diff --git a/poetry.lock b/poetry.lock
index f251abe7..363dfe51 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -1,5 +1,16 @@
 # This file is automatically @generated by Poetry 1.7.1 and should not be changed by hand.
 
+[[package]]
+name = "absl-py"
+version = "2.1.0"
+description = "Abseil Python Common Libraries, see https://github.com/abseil/abseil-py."
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "absl-py-2.1.0.tar.gz", hash = "sha256:7820790efbb316739cde8b4e19357243fc3608a152024288513dd968d7d959ff"},
+    {file = "absl_py-2.1.0-py3-none-any.whl", hash = "sha256:526a04eadab8b4ee719ce68f204172ead1027549089702d99b9059f129ff1308"},
+]
+
 [[package]]
 name = "accelerate"
 version = "0.33.0"
@@ -141,6 +152,7 @@ files = [
 [package.dependencies]
 aiohappyeyeballs = ">=2.3.0"
 aiosignal = ">=1.1.2"
+async-timeout = {version = ">=4.0,<5.0", markers = "python_version < \"3.11\""}
 attrs = ">=17.3.0"
 frozenlist = ">=1.1.1"
 multidict = ">=4.5,<7.0"
@@ -149,6 +161,17 @@ yarl = ">=1.0,<2.0"
 [package.extras]
 speedups = ["Brotli", "aiodns (>=3.2.0)", "brotlicffi"]
 
+[[package]]
+name = "aiolimiter"
+version = "1.1.0"
+description = "asyncio rate limiter, a leaky bucket implementation"
+optional = false
+python-versions = ">=3.7,<4.0"
+files = [
+    {file = "aiolimiter-1.1.0-py3-none-any.whl", hash = "sha256:0b4997961fc58b8df40279e739f9cf0d3e255e63e9a44f64df567a8c17241e24"},
+    {file = "aiolimiter-1.1.0.tar.gz", hash = "sha256:461cf02f82a29347340d031626c92853645c099cb5ff85577b831a7bd21132b5"},
+]
+
 [[package]]
 name = "aiosignal"
 version = "1.3.1"
@@ -185,6 +208,31 @@ files = [
     {file = "ansicon-1.89.0.tar.gz", hash = "sha256:e4d039def5768a47e4afec8e89e83ec3ae5a26bf00ad851f914d1240b444d2b1"},
 ]
 
+[[package]]
+name = "anthropic"
+version = "0.34.0"
+description = "The official Python library for the anthropic API"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "anthropic-0.34.0-py3-none-any.whl", hash = "sha256:4f4b3b5cb7647f5879ee72c22543a10af6da83b18c8401938053b9b4965a9595"},
+    {file = "anthropic-0.34.0.tar.gz", hash = "sha256:820d6cc77cfcbbe56f0920a58f7e2bacf119b9e80f6de1bf92a422799ee4680f"},
+]
+
+[package.dependencies]
+anyio = ">=3.5.0,<5"
+distro = ">=1.7.0,<2"
+httpx = ">=0.23.0,<1"
+jiter = ">=0.4.0,<1"
+pydantic = ">=1.9.0,<3"
+sniffio = "*"
+tokenizers = ">=0.13.0"
+typing-extensions = ">=4.7,<5"
+
+[package.extras]
+bedrock = ["boto3 (>=1.28.57)", "botocore (>=1.31.57)"]
+vertex = ["google-auth (>=2,<3)"]
+
 [[package]]
 name = "anyio"
 version = "4.4.0"
@@ -197,8 +245,10 @@ files = [
 ]
 
 [package.dependencies]
+exceptiongroup = {version = ">=1.0.2", markers = "python_version < \"3.11\""}
 idna = ">=2.8"
 sniffio = ">=1.1"
+typing-extensions = {version = ">=4.1", markers = "python_version < \"3.11\""}
 
 [package.extras]
 doc = ["Sphinx (>=7)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme"]
@@ -238,6 +288,43 @@ types-python-dateutil = ">=2.8.10"
 doc = ["doc8", "sphinx (>=7.0.0)", "sphinx-autobuild", "sphinx-autodoc-typehints", "sphinx_rtd_theme (>=1.3.0)"]
 test = ["dateparser (==1.*)", "pre-commit", "pytest", "pytest-cov", "pytest-mock", "pytz (==2021.1)", "simplejson (==3.*)"]
 
+[[package]]
+name = "asn1crypto"
+version = "1.5.1"
+description = "Fast ASN.1 parser and serializer with definitions for private keys, public keys, certificates, CRL, OCSP, CMS, PKCS#3, PKCS#7, PKCS#8, PKCS#12, PKCS#5, X.509 and TSP"
+optional = false
+python-versions = "*"
+files = [
+    {file = "asn1crypto-1.5.1-py2.py3-none-any.whl", hash = "sha256:db4e40728b728508912cbb3d44f19ce188f218e9eba635821bb4b68564f8fd67"},
+    {file = "asn1crypto-1.5.1.tar.gz", hash = "sha256:13ae38502be632115abf8a24cbe5f4da52e3b5231990aff31123c805306ccb9c"},
+]
+
+[[package]]
+name = "astunparse"
+version = "1.6.3"
+description = "An AST unparser for Python"
+optional = false
+python-versions = "*"
+files = [
+    {file = "astunparse-1.6.3-py2.py3-none-any.whl", hash = "sha256:c2652417f2c8b5bb325c885ae329bdf3f86424075c4fd1a128674bc6fba4b8e8"},
+    {file = "astunparse-1.6.3.tar.gz", hash = "sha256:5ad93a8456f0d084c3456d059fd9a92cce667963232cbf763eac3bc5b7940872"},
+]
+
+[package.dependencies]
+six = ">=1.6.1,<2.0"
+wheel = ">=0.23.0,<1.0"
+
+[[package]]
+name = "async-timeout"
+version = "4.0.3"
+description = "Timeout context manager for asyncio programs"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "async-timeout-4.0.3.tar.gz", hash = "sha256:4640d96be84d82d02ed59ea2b7105a0f7b33abe8703703cd0ab0bf87c427522f"},
+    {file = "async_timeout-4.0.3-py3-none-any.whl", hash = "sha256:7405140ff1230c310e51dc27b3145b9092d659ce68ff733fb0cefe3ee42be028"},
+]
+
 [[package]]
 name = "attrs"
 version = "24.2.0"
@@ -284,6 +371,7 @@ files = [
 
 [package.dependencies]
 pyflakes = ">=3.0.0"
+tomli = {version = ">=2.0.1", markers = "python_version < \"3.11\""}
 
 [[package]]
 name = "azure-core"
@@ -413,6 +501,24 @@ files = [
 tests = ["pytest (>=3.2.1,!=3.3.0)"]
 typecheck = ["mypy"]
 
+[[package]]
+name = "beartype"
+version = "0.18.5"
+description = "Unbearably fast runtime type checking in pure Python."
+optional = false
+python-versions = ">=3.8.0"
+files = [
+    {file = "beartype-0.18.5-py3-none-any.whl", hash = "sha256:5301a14f2a9a5540fe47ec6d34d758e9cd8331d36c4760fc7a5499ab86310089"},
+    {file = "beartype-0.18.5.tar.gz", hash = "sha256:264ddc2f1da9ec94ff639141fbe33d22e12a9f75aa863b83b7046ffff1381927"},
+]
+
+[package.extras]
+all = ["typing-extensions (>=3.10.0.0)"]
+dev = ["autoapi (>=0.9.0)", "coverage (>=5.5)", "equinox", "mypy (>=0.800)", "numpy", "pandera", "pydata-sphinx-theme (<=0.7.2)", "pytest (>=4.0.0)", "sphinx", "sphinx (>=4.2.0,<6.0.0)", "sphinxext-opengraph (>=0.7.5)", "tox (>=3.20.1)", "typing-extensions (>=3.10.0.0)"]
+doc-rtd = ["autoapi (>=0.9.0)", "pydata-sphinx-theme (<=0.7.2)", "sphinx (>=4.2.0,<6.0.0)", "sphinxext-opengraph (>=0.7.5)"]
+test-tox = ["equinox", "mypy (>=0.800)", "numpy", "pandera", "pytest (>=4.0.0)", "sphinx", "typing-extensions (>=3.10.0.0)"]
+test-tox-coverage = ["coverage (>=5.5)"]
+
 [[package]]
 name = "bitsandbytes"
 version = "0.42.0"
@@ -464,6 +570,8 @@ mypy-extensions = ">=0.4.3"
 packaging = ">=22.0"
 pathspec = ">=0.9.0"
 platformdirs = ">=2"
+tomli = {version = ">=1.1.0", markers = "python_version < \"3.11\""}
+typing-extensions = {version = ">=4.0.1", markers = "python_version < \"3.11\""}
 
 [package.extras]
 colorama = ["colorama (>=0.4.3)"]
@@ -487,6 +595,80 @@ jinxed = {version = ">=1.1.0", markers = "platform_system == \"Windows\""}
 six = ">=1.9.0"
 wcwidth = ">=0.1.4"
 
+[[package]]
+name = "blinker"
+version = "1.8.2"
+description = "Fast, simple object-to-object and broadcast signaling"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "blinker-1.8.2-py3-none-any.whl", hash = "sha256:1779309f71bf239144b9399d06ae925637cf6634cf6bd131104184531bf67c01"},
+    {file = "blinker-1.8.2.tar.gz", hash = "sha256:8f77b09d3bf7c795e969e9486f39c2c5e9c39d4ee07424be2bc594ece9642d83"},
+]
+
+[[package]]
+name = "blis"
+version = "0.7.11"
+description = "The Blis BLAS-like linear algebra library, as a self-contained C-extension."
+optional = false
+python-versions = "*"
+files = [
+    {file = "blis-0.7.11-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:cd5fba34c5775e4c440d80e4dea8acb40e2d3855b546e07c4e21fad8f972404c"},
+    {file = "blis-0.7.11-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:31273d9086cab9c56986d478e3ed6da6752fa4cdd0f7b5e8e5db30827912d90d"},
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+    {file = "blis-0.7.11-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ee493683e3043650d4413d531e79e580d28a3c7bdd184f1b9cfa565497bda1e7"},
+    {file = "blis-0.7.11-cp310-cp310-win_amd64.whl", hash = "sha256:a73945a9d635eea528bccfdfcaa59dd35bd5f82a4a40d5ca31f08f507f3a6f81"},
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+    {file = "blis-0.7.11-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:2ff7abd784033836b284ff9f4d0d7cb0737b7684daebb01a4c9fe145ffa5a31e"},
+    {file = "blis-0.7.11-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:f9caffcd14795bfe52add95a0dd8426d44e737b55fcb69e2b797816f4da0b1d2"},
+    {file = "blis-0.7.11-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:2fb36989ed61233cfd48915896802ee6d3d87882190000f8cfe0cf4a3819f9a8"},
+    {file = "blis-0.7.11-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7ea09f961871f880d5dc622dce6c370e4859559f0ead897ae9b20ddafd6b07a2"},
+    {file = "blis-0.7.11-cp39-cp39-win_amd64.whl", hash = "sha256:5bb38adabbb22f69f22c74bad025a010ae3b14de711bf5c715353980869d491d"},
+    {file = "blis-0.7.11.tar.gz", hash = "sha256:cec6d48f75f7ac328ae1b6fbb372dde8c8a57c89559172277f66e01ff08d4d42"},
+]
+
+[package.dependencies]
+numpy = {version = ">=1.19.0", markers = "python_version >= \"3.9\""}
+
+[[package]]
+name = "blobfile"
+version = "2.1.1"
+description = "Read GCS, ABS and local paths with the same interface, clone of tensorflow.io.gfile"
+optional = false
+python-versions = ">=3.8.0"
+files = [
+    {file = "blobfile-2.1.1-py3-none-any.whl", hash = "sha256:fde52ebfaac236a52e61b0da34e5cff27e8afdedc4b6b732d30ed19187128434"},
+    {file = "blobfile-2.1.1.tar.gz", hash = "sha256:37a77de8c6ded9e1d97265c4d9b1c2145337a12b8eac1a4203fc895fb696e261"},
+]
+
+[package.dependencies]
+filelock = ">=3.0,<4.0"
+lxml = ">=4.9,<5.0"
+pycryptodomex = ">=3.8,<4.0"
+urllib3 = ">=1.25.3,<3"
+
 [[package]]
 name = "boto3"
 version = "1.35.0"
@@ -628,6 +810,17 @@ files = [
     {file = "cachetools-5.4.0.tar.gz", hash = "sha256:b8adc2e7c07f105ced7bc56dbb6dfbe7c4a00acce20e2227b3f355be89bc6827"},
 ]
 
+[[package]]
+name = "catalogue"
+version = "2.0.10"
+description = "Super lightweight function registries for your library"
+optional = false
+python-versions = ">=3.6"
+files = [
+    {file = "catalogue-2.0.10-py3-none-any.whl", hash = "sha256:58c2de0020aa90f4a2da7dfad161bf7b3b054c86a5f09fcedc0b2b740c109a9f"},
+    {file = "catalogue-2.0.10.tar.gz", hash = "sha256:4f56daa940913d3f09d589c191c74e5a6d51762b3a9e37dd53b7437afd6cda15"},
+]
+
 [[package]]
 name = "certifi"
 version = "2024.7.4"
@@ -817,6 +1010,17 @@ files = [
     {file = "charset_normalizer-3.3.2-py3-none-any.whl", hash = "sha256:3e4d1f6587322d2788836a99c69062fbb091331ec940e02d12d179c1d53e25fc"},
 ]
 
+[[package]]
+name = "chess"
+version = "1.10.0"
+description = "A chess library with move generation and validation, Polyglot opening book probing, PGN reading and writing, Gaviota tablebase probing, Syzygy tablebase probing, and XBoard/UCI engine communication."
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "chess-1.10.0-py3-none-any.whl", hash = "sha256:48ff7c084a370811819cfc753c2ee159942356ada70824666bd01ee3fca170d0"},
+    {file = "chess-1.10.0.tar.gz", hash = "sha256:bccde105f54aa436e899f92b4ba953731c65012a863fd9235683d0e2863ccd54"},
+]
+
 [[package]]
 name = "circuitbreaker"
 version = "2.0.0"
@@ -842,6 +1046,37 @@ files = [
 [package.dependencies]
 colorama = {version = "*", markers = "platform_system == \"Windows\""}
 
+[[package]]
+name = "cloudpathlib"
+version = "0.18.1"
+description = "pathlib-style classes for cloud storage services."
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "cloudpathlib-0.18.1-py3-none-any.whl", hash = "sha256:20efd5d772c75df91bb2ac52e053be53fd9000f5e9755fd92375a2a9fe6005e0"},
+    {file = "cloudpathlib-0.18.1.tar.gz", hash = "sha256:ffd22f324bfbf9c3f2bc1bec6e8372cb372a0feef17c7f2b48030cd6810ea859"},
+]
+
+[package.dependencies]
+typing_extensions = {version = ">4", markers = "python_version < \"3.11\""}
+
+[package.extras]
+all = ["cloudpathlib[azure]", "cloudpathlib[gs]", "cloudpathlib[s3]"]
+azure = ["azure-storage-blob (>=12)"]
+gs = ["google-cloud-storage"]
+s3 = ["boto3"]
+
+[[package]]
+name = "cloudpickle"
+version = "3.0.0"
+description = "Pickler class to extend the standard pickle.Pickler functionality"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "cloudpickle-3.0.0-py3-none-any.whl", hash = "sha256:246ee7d0c295602a036e86369c77fecda4ab17b506496730f2f576d9016fd9c7"},
+    {file = "cloudpickle-3.0.0.tar.gz", hash = "sha256:996d9a482c6fb4f33c1a35335cf8afd065d2a56e973270364840712d9131a882"},
+]
+
 [[package]]
 name = "colorama"
 version = "0.4.6"
@@ -853,6 +1088,21 @@ files = [
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+description = "The sweetest config system for Python"
+optional = false
+python-versions = ">=3.6"
+files = [
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+srsly = ">=2.4.0,<3.0.0"
+
 [[package]]
 name = "contourpy"
 version = "1.2.1"
@@ -1097,6 +1347,61 @@ files = [
 docs = ["ipython", "matplotlib", "numpydoc", "sphinx"]
 tests = ["pytest", "pytest-cov", "pytest-xdist"]
 
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+    {file = "cymem-2.0.8-cp39-cp39-win_amd64.whl", hash = "sha256:ceeab3ce2a92c7f3b2d90854efb32cb203e78cb24c836a5a9a2cac221930303b"},
+    {file = "cymem-2.0.8.tar.gz", hash = "sha256:8fb09d222e21dcf1c7e907dc85cf74501d4cea6c4ed4ac6c9e016f98fb59cbbf"},
+]
+
+[[package]]
+name = "dacite"
+version = "1.8.1"
+description = "Simple creation of data classes from dictionaries."
+optional = false
+python-versions = ">=3.6"
+files = [
+    {file = "dacite-1.8.1-py3-none-any.whl", hash = "sha256:cc31ad6fdea1f49962ea42db9421772afe01ac5442380d9a99fcf3d188c61afe"},
+]
+
+[package.extras]
+dev = ["black", "coveralls", "mypy", "pre-commit", "pylint", "pytest (>=5)", "pytest-benchmark", "pytest-cov"]
+
 [[package]]
 name = "dataclasses-json"
 version = "0.6.7"
@@ -1193,6 +1498,28 @@ files = [
     {file = "distro-1.9.0.tar.gz", hash = "sha256:2fa77c6fd8940f116ee1d6b94a2f90b13b5ea8d019b98bc8bafdcabcdd9bdbed"},
 ]
 
+[[package]]
+name = "docker"
+version = "7.1.0"
+description = "A Python library for the Docker Engine API."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "docker-7.1.0-py3-none-any.whl", hash = "sha256:c96b93b7f0a746f9e77d325bcfb87422a3d8bd4f03136ae8a85b37f1898d5fc0"},
+    {file = "docker-7.1.0.tar.gz", hash = "sha256:ad8c70e6e3f8926cb8a92619b832b4ea5299e2831c14284663184e200546fa6c"},
+]
+
+[package.dependencies]
+pywin32 = {version = ">=304", markers = "sys_platform == \"win32\""}
+requests = ">=2.26.0"
+urllib3 = ">=1.26.0"
+
+[package.extras]
+dev = ["coverage (==7.2.7)", "pytest (==7.4.2)", "pytest-cov (==4.1.0)", "pytest-timeout (==2.1.0)", "ruff (==0.1.8)"]
+docs = ["myst-parser (==0.18.0)", "sphinx (==5.1.1)"]
+ssh = ["paramiko (>=2.4.3)"]
+websockets = ["websocket-client (>=1.3.0)"]
+
 [[package]]
 name = "docker-pycreds"
 version = "0.4.0"
@@ -1218,6 +1545,134 @@ files = [
     {file = "docstring_parser-0.16.tar.gz", hash = "sha256:538beabd0af1e2db0146b6bd3caa526c35a34d61af9fd2887f3a8a27a739aa6e"},
 ]
 
+[[package]]
+name = "evals"
+version = "3.0.1.post1"
+description = ""
+optional = false
+python-versions = ">=3.9"
+files = []
+develop = false
+
+[package.dependencies]
+aiolimiter = "*"
+anthropic = "*"
+backoff = "*"
+beartype = ">=0.12.0"
+blobfile = "*"
+chess = "*"
+dacite = "*"
+datasets = "*"
+docker = "*"
+evaluate = "*"
+filelock = "*"
+fire = "*"
+flask = "*"
+google-generativeai = "*"
+gymnasium = "*"
+jiwer = "*"
+langchain = "*"
+langdetect = "*"
+librosa = "*"
+lz4 = "*"
+matplotlib = "*"
+mock = "*"
+mypy = "*"
+networkx = "*"
+nltk = "*"
+numexpr = "*"
+numpy = "*"
+openai = ">=1.0.0"
+pandas = "*"
+peft = "*"
+playwright = "*"
+pydantic = "*"
+pytest = "*"
+pyyaml = "*"
+sacrebleu = "*"
+seaborn = "*"
+snowflake-connector-python = {version = "*", extras = ["pandas"]}
+soundfile = "*"
+spacy-universal-sentence-encoder = "*"
+statsmodels = "*"
+termcolor = "*"
+tiktoken = "*"
+tqdm = "*"
+transformers = {version = "*", extras = ["torch"]}
+types-PyYAML = "*"
+types-tqdm = "*"
+zstandard = "*"
+
+[package.extras]
+formatters = ["autoflake", "black", "isort", "ruff"]
+torch = ["torch"]
+
+[package.source]
+type = "git"
+url = "https://github.com/fixie-ai/evals"
+reference = "HEAD"
+resolved_reference = "908a814c0881d99d4876d7000878ec0760a22311"
+
+[[package]]
+name = "evaluate"
+version = "0.4.2"
+description = "HuggingFace community-driven open-source library of evaluation"
+optional = false
+python-versions = ">=3.8.0"
+files = [
+    {file = "evaluate-0.4.2-py3-none-any.whl", hash = "sha256:5fdcaf8a086b075c2b8e2c5898f501224b020b0ac7d07be76536e47e661c0c65"},
+    {file = "evaluate-0.4.2.tar.gz", hash = "sha256:851ab767df8ec4031366c512eb88d8174adfba65d2c8c4c9bfdfe9c702212234"},
+]
+
+[package.dependencies]
+datasets = ">=2.0.0"
+dill = "*"
+fsspec = {version = ">=2021.05.0", extras = ["http"]}
+huggingface-hub = ">=0.7.0"
+multiprocess = "*"
+numpy = ">=1.17"
+packaging = "*"
+pandas = "*"
+requests = ">=2.19.0"
+tqdm = ">=4.62.1"
+xxhash = "*"
+
+[package.extras]
+dev = ["Werkzeug (>=1.0.1)", "absl-py", "accelerate", "bert-score (>=0.3.6)", "black (>=22.0,<23.0)", "cer (>=1.2.0)", "charcut (>=1.1.1)", "flake8 (>=3.8.3)", "isort (>=5.0.0)", "jiwer", "mauve-text", "nltk", "pytest", "pytest-datadir", "pytest-xdist", "pyyaml (>=5.3.1)", "requests-file (>=1.5.1)", "rouge-score (>=0.1.2)", "sacrebleu", "sacremoses", "scikit-learn", "scipy (>=1.10.0)", "sentencepiece", "seqeval", "six (>=1.15.0,<1.16.0)", "tensorflow (>=2.3,!=2.6.0,!=2.6.1,<=2.10)", "texttable (>=1.6.3)", "tldextract (>=3.1.0)", "toml (>=0.10.1)", "torch", "transformers", "trectools", "unidecode (>=1.3.4)"]
+docs = ["s3fs"]
+evaluator = ["scipy (>=1.7.1)", "transformers"]
+quality = ["black (>=22.0,<23.0)", "flake8 (>=3.8.3)", "isort (>=5.0.0)", "pyyaml (>=5.3.1)"]
+template = ["cookiecutter", "gradio (>=3.0.0)"]
+tensorflow = ["tensorflow (>=2.2.0,!=2.6.0,!=2.6.1)"]
+tensorflow-gpu = ["tensorflow-gpu (>=2.2.0,!=2.6.0,!=2.6.1)"]
+tests = ["Werkzeug (>=1.0.1)", "absl-py", "accelerate", "bert-score (>=0.3.6)", "cer (>=1.2.0)", "charcut (>=1.1.1)", "jiwer", "mauve-text", "nltk", "pytest", "pytest-datadir", "pytest-xdist", "requests-file (>=1.5.1)", "rouge-score (>=0.1.2)", "sacrebleu", "sacremoses", "scikit-learn", "scipy (>=1.10.0)", "sentencepiece", "seqeval", "six (>=1.15.0,<1.16.0)", "tensorflow (>=2.3,!=2.6.0,!=2.6.1,<=2.10)", "texttable (>=1.6.3)", "tldextract (>=3.1.0)", "toml (>=0.10.1)", "torch", "transformers", "trectools", "unidecode (>=1.3.4)"]
+torch = ["torch"]
+
+[[package]]
+name = "exceptiongroup"
+version = "1.2.2"
+description = "Backport of PEP 654 (exception groups)"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "exceptiongroup-1.2.2-py3-none-any.whl", hash = "sha256:3111b9d131c238bec2f8f516e123e14ba243563fb135d3fe885990585aa7795b"},
+    {file = "exceptiongroup-1.2.2.tar.gz", hash = "sha256:47c2edf7c6738fafb49fd34290706d1a1a2f4d1c6df275526b62cbb4aa5393cc"},
+]
+
+[package.extras]
+test = ["pytest (>=6)"]
+
+[[package]]
+name = "farama-notifications"
+version = "0.0.4"
+description = "Notifications for all Farama Foundation maintained libraries."
+optional = false
+python-versions = "*"
+files = [
+    {file = "Farama-Notifications-0.0.4.tar.gz", hash = "sha256:13fceff2d14314cf80703c8266462ebf3733c7d165336eee998fc58e545efd18"},
+    {file = "Farama_Notifications-0.0.4-py3-none-any.whl", hash = "sha256:14de931035a41961f7c056361dc7f980762a143d05791ef5794a751a2caf05ae"},
+]
+
 [[package]]
 name = "fastapi"
 version = "0.112.1"
@@ -1265,6 +1720,53 @@ docs = ["furo (>=2023.9.10)", "sphinx (>=7.2.6)", "sphinx-autodoc-typehints (>=1
 testing = ["covdefaults (>=2.3)", "coverage (>=7.3.2)", "diff-cover (>=8.0.1)", "pytest (>=7.4.3)", "pytest-asyncio (>=0.21)", "pytest-cov (>=4.1)", "pytest-mock (>=3.12)", "pytest-timeout (>=2.2)", "virtualenv (>=20.26.2)"]
 typing = ["typing-extensions (>=4.8)"]
 
+[[package]]
+name = "fire"
+version = "0.6.0"
+description = "A library for automatically generating command line interfaces."
+optional = false
+python-versions = "*"
+files = [
+    {file = "fire-0.6.0.tar.gz", hash = "sha256:54ec5b996ecdd3c0309c800324a0703d6da512241bc73b553db959d98de0aa66"},
+]
+
+[package.dependencies]
+six = "*"
+termcolor = "*"
+
+[[package]]
+name = "flask"
+version = "3.0.3"
+description = "A simple framework for building complex web applications."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "flask-3.0.3-py3-none-any.whl", hash = "sha256:34e815dfaa43340d1d15a5c3a02b8476004037eb4840b34910c6e21679d288f3"},
+    {file = "flask-3.0.3.tar.gz", hash = "sha256:ceb27b0af3823ea2737928a4d99d125a06175b8512c445cbd9a9ce200ef76842"},
+]
+
+[package.dependencies]
+blinker = ">=1.6.2"
+click = ">=8.1.3"
+itsdangerous = ">=2.1.2"
+Jinja2 = ">=3.1.2"
+Werkzeug = ">=3.0.0"
+
+[package.extras]
+async = ["asgiref (>=3.2)"]
+dotenv = ["python-dotenv"]
+
+[[package]]
+name = "flatbuffers"
+version = "24.3.25"
+description = "The FlatBuffers serialization format for Python"
+optional = false
+python-versions = "*"
+files = [
+    {file = "flatbuffers-24.3.25-py2.py3-none-any.whl", hash = "sha256:8dbdec58f935f3765e4f7f3cf635ac3a77f83568138d6a2311f524ec96364812"},
+    {file = "flatbuffers-24.3.25.tar.gz", hash = "sha256:de2ec5b203f21441716617f38443e0a8ebf3d25bf0d9c0bb0ce68fa00ad546a4"},
+]
+
 [[package]]
 name = "fonttools"
 version = "4.53.1"
@@ -1454,6 +1956,16 @@ smb = ["smbprotocol"]
 ssh = ["paramiko"]
 tqdm = ["tqdm"]
 
+[[package]]
+name = "gast"
+version = "0.6.0"
+description = "Python AST that abstracts the underlying Python version"
+optional = false
+python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,>=2.7"
+files = [
+    {file = "gast-0.6.0.tar.gz", hash = "sha256:88fc5300d32c7ac6ca7b515310862f71e6fdf2c029bbec7c66c0f5dd47b6b1fb"},
+]
+
 [[package]]
 name = "gcsfs"
 version = "2024.3.1"
@@ -1510,6 +2022,23 @@ gitdb = ">=4.0.1,<5"
 doc = ["sphinx (==4.3.2)", "sphinx-autodoc-typehints", "sphinx-rtd-theme", "sphinxcontrib-applehelp (>=1.0.2,<=1.0.4)", "sphinxcontrib-devhelp (==1.0.2)", "sphinxcontrib-htmlhelp (>=2.0.0,<=2.0.1)", "sphinxcontrib-qthelp (==1.0.3)", "sphinxcontrib-serializinghtml (==1.1.5)"]
 test = ["coverage[toml]", "ddt (>=1.1.1,!=1.4.3)", "mock", "mypy", "pre-commit", "pytest (>=7.3.1)", "pytest-cov", "pytest-instafail", "pytest-mock", "pytest-sugar", "typing-extensions"]
 
+[[package]]
+name = "google-ai-generativelanguage"
+version = "0.6.6"
+description = "Google Ai Generativelanguage API client library"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "google-ai-generativelanguage-0.6.6.tar.gz", hash = "sha256:1739f035caeeeca5c28f887405eec8690f3372daf79fecf26454a97a4f1733a8"},
+    {file = "google_ai_generativelanguage-0.6.6-py3-none-any.whl", hash = "sha256:59297737931f073d55ce1268dcc6d95111ee62850349d2b6cde942b16a4fca5c"},
+]
+
+[package.dependencies]
+google-api-core = {version = ">=1.34.1,<2.0.dev0 || >=2.11.dev0,<3.0.0dev", extras = ["grpc"]}
+google-auth = ">=2.14.1,<2.24.0 || >2.24.0,<2.25.0 || >2.25.0,<3.0.0dev"
+proto-plus = ">=1.22.3,<2.0.0dev"
+protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.0 || >4.21.0,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<5.0.0dev"
+
 [[package]]
 name = "google-api-core"
 version = "2.19.1"
@@ -1524,6 +2053,14 @@ files = [
 [package.dependencies]
 google-auth = ">=2.14.1,<3.0.dev0"
 googleapis-common-protos = ">=1.56.2,<2.0.dev0"
+grpcio = [
+    {version = ">=1.49.1,<2.0dev", optional = true, markers = "python_version >= \"3.11\" and extra == \"grpc\""},
+    {version = ">=1.33.2,<2.0dev", optional = true, markers = "python_version < \"3.11\" and extra == \"grpc\""},
+]
+grpcio-status = [
+    {version = ">=1.49.1,<2.0.dev0", optional = true, markers = "python_version >= \"3.11\" and extra == \"grpc\""},
+    {version = ">=1.33.2,<2.0.dev0", optional = true, markers = "python_version < \"3.11\" and extra == \"grpc\""},
+]
 proto-plus = ">=1.22.3,<2.0.0dev"
 protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.0 || >4.21.0,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<6.0.0.dev0"
 requests = ">=2.18.0,<3.0.0.dev0"
@@ -1533,6 +2070,24 @@ grpc = ["grpcio (>=1.33.2,<2.0dev)", "grpcio (>=1.49.1,<2.0dev)", "grpcio-status
 grpcgcp = ["grpcio-gcp (>=0.2.2,<1.0.dev0)"]
 grpcio-gcp = ["grpcio-gcp (>=0.2.2,<1.0.dev0)"]
 
+[[package]]
+name = "google-api-python-client"
+version = "2.141.0"
+description = "Google API Client Library for Python"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "google_api_python_client-2.141.0-py2.py3-none-any.whl", hash = "sha256:43c05322b91791204465291b3852718fae38d4f84b411d8be847c4f86882652a"},
+    {file = "google_api_python_client-2.141.0.tar.gz", hash = "sha256:0f225b1f45d5a6f8c2a400f48729f5d6da9a81138e81e0478d61fdd8edf6563a"},
+]
+
+[package.dependencies]
+google-api-core = ">=1.31.5,<2.0.dev0 || >2.3.0,<3.0.0.dev0"
+google-auth = ">=1.32.0,<2.24.0 || >2.24.0,<2.25.0 || >2.25.0,<3.0.0.dev0"
+google-auth-httplib2 = ">=0.2.0,<1.0.0"
+httplib2 = ">=0.19.0,<1.dev0"
+uritemplate = ">=3.0.1,<5"
+
 [[package]]
 name = "google-auth"
 version = "2.33.0"
@@ -1556,6 +2111,21 @@ pyopenssl = ["cryptography (>=38.0.3)", "pyopenssl (>=20.0.0)"]
 reauth = ["pyu2f (>=0.1.5)"]
 requests = ["requests (>=2.20.0,<3.0.0.dev0)"]
 
+[[package]]
+name = "google-auth-httplib2"
+version = "0.2.0"
+description = "Google Authentication Library: httplib2 transport"
+optional = false
+python-versions = "*"
+files = [
+    {file = "google-auth-httplib2-0.2.0.tar.gz", hash = "sha256:38aa7badf48f974f1eb9861794e9c0cb2a0511a4ec0679b1f886d108f5640e05"},
+    {file = "google_auth_httplib2-0.2.0-py2.py3-none-any.whl", hash = "sha256:b65a0a2123300dd71281a7bf6e64d65a0759287df52729bdd1ae2e47dc311a3d"},
+]
+
+[package.dependencies]
+google-auth = "*"
+httplib2 = ">=0.19.0"
+
 [[package]]
 name = "google-auth-oauthlib"
 version = "1.2.1"
@@ -1693,6 +2263,44 @@ files = [
 [package.extras]
 testing = ["pytest"]
 
+[[package]]
+name = "google-generativeai"
+version = "0.7.2"
+description = "Google Generative AI High level API client library and tools."
+optional = false
+python-versions = ">=3.9"
+files = [
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+]
+
+[package.dependencies]
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+google-api-core = "*"
+google-api-python-client = "*"
+google-auth = ">=2.15.0"
+protobuf = "*"
+pydantic = "*"
+tqdm = "*"
+typing-extensions = "*"
+
+[package.extras]
+dev = ["Pillow", "absl-py", "black", "ipython", "nose2", "pandas", "pytype", "pyyaml"]
+
+[[package]]
+name = "google-pasta"
+version = "0.2.0"
+description = "pasta is an AST-based Python refactoring library"
+optional = false
+python-versions = "*"
+files = [
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+]
+
+[package.dependencies]
+six = "*"
+
 [[package]]
 name = "google-resumable-media"
 version = "2.7.2"
@@ -1817,38 +2425,213 @@ urllib3 = ">=2.0,<3.0"
 uvicorn = {version = ">=0.14.0", markers = "sys_platform != \"emscripten\""}
 
 [package.extras]
-oauth = ["authlib", "itsdangerous"]
+oauth = ["authlib", "itsdangerous"]
+
+[[package]]
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+version = "1.3.0"
+description = "Python library for easily interacting with trained machine learning models"
+optional = false
+python-versions = ">=3.8"
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+
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+httpx = ">=0.24.1"
+huggingface-hub = ">=0.19.3"
+packaging = "*"
+typing-extensions = ">=4.0,<5.0"
+websockets = ">=10.0,<13.0"
+
+[[package]]
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+version = "3.2.3"
+description = "GraphQL implementation for Python, a port of GraphQL.js, the JavaScript reference implementation for GraphQL."
+optional = false
+python-versions = ">=3.6,<4"
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+
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+optional = false
+python-versions = ">=3.6"
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+protobuf = ">=4.21.6"
 
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+
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+other = ["lz4 (>=3.1.0)", "matplotlib (>=3.0)", "moviepy (>=1.0.0)", "opencv-python (>=3.0)", "torch (>=1.0.0)"]
+testing = ["pytest (==7.1.3)", "scipy (>=1.7.3)"]
+toy-text = ["pygame (>=2.1.3)", "pygame (>=2.1.3)"]
+
 [[package]]
 name = "h11"
 version = "0.14.0"
@@ -1860,6 +2643,39 @@ files = [
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 ]
 
+[[package]]
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+python-versions = ">=3.8"
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+
+[package.dependencies]
+numpy = ">=1.17.3"
+
 [[package]]
 name = "httpcore"
 version = "1.0.5"
@@ -1881,6 +2697,20 @@ http2 = ["h2 (>=3,<5)"]
 socks = ["socksio (==1.*)"]
 trio = ["trio (>=0.22.0,<0.26.0)"]
 
+[[package]]
+name = "httplib2"
+version = "0.22.0"
+description = "A comprehensive HTTP client library."
+optional = false
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
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+
 [[package]]
 name = "httpx"
 version = "0.27.0"
@@ -2004,6 +2834,17 @@ files = [
 [package.extras]
 colors = ["colorama (>=0.4.6)"]
 
+[[package]]
+name = "itsdangerous"
+version = "2.2.0"
+description = "Safely pass data to untrusted environments and back."
+optional = false
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+
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 version = "3.0.4"
@@ -2072,6 +2983,27 @@ files = [
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+optional = false
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+numpy = "*"
+optree = "*"
+packaging = "*"
+rich = "*"
+
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 name = "kiwisolver"
 version = "1.4.5"
@@ -2185,6 +3117,78 @@ files = [
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+
+[package.extras]
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+llms = ["cohere", "huggingface-hub", "nlpcloud", "openai"]
+
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+version = "3.4.0"
+description = "Tools for labeling human languages with IETF language tags"
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+
+[package.extras]
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+test = ["pytest", "pytest-cov"]
+
+[[package]]
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+version = "1.0.9"
+description = "Language detection library ported from Google's language-detection."
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+[package.dependencies]
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+
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+description = "Supplementary data about languages used by the langcodes module"
+optional = false
+python-versions = "*"
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+
+[package.extras]
+build = ["build", "twine"]
+test = ["pytest", "pytest-cov"]
+
 [[package]]
 name = "lazy-loader"
 version = "0.4"
@@ -2204,6 +3208,25 @@ dev = ["changelist (==0.5)"]
 lint = ["pre-commit (==3.7.0)"]
 test = ["pytest (>=7.4)", "pytest-cov (>=4.1)"]
 
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+
+[package.extras]
+test = ["hypothesis", "pytest", "readme-renderer"]
+
+[[package]]
+name = "markdown"
+version = "3.7"
+description = "Python implementation of John Gruber's Markdown."
+optional = false
+python-versions = ">=3.8"
+files = [
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+testing = ["coverage", "pyyaml"]
 
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 name = "markdown-it-py"
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+description = ""
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+python-versions = ">=3.9"
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+[package.extras]
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+
+[[package]]
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+docs = ["sphinx"]
+test = ["pytest", "pytest-cov"]
+
 [[package]]
 name = "mosaicml-cli"
 version = "0.6.41"
@@ -2916,6 +4113,48 @@ files = [
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 dill = ">=0.3.8"
 
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 [[package]]
 name = "mypy"
 version = "1.10.1"
@@ -2954,6 +4193,7 @@ files = [
 
 [package.dependencies]
 mypy-extensions = ">=1.0.0"
+tomli = {version = ">=1.1.0", markers = "python_version < \"3.11\""}
 typing-extensions = ">=4.1.0"
 
 [package.extras]
@@ -2973,6 +4213,17 @@ files = [
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 ]
 
+[[package]]
+name = "namex"
+version = "0.0.8"
+description = "A simple utility to separate the implementation of your Python package and its public API surface."
+optional = false
+python-versions = "*"
+files = [
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+
 [[package]]
 name = "networkx"
 version = "3.3"
@@ -3050,6 +4301,47 @@ files = [
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 numpy = ">=1.22,<2.1"
 
+[[package]]
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+version = "2.10.1"
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 ]
 
+[[package]]
+name = "patsy"
+version = "0.5.6"
+description = "A Python package for describing statistical models and for building design matrices."
+optional = false
+python-versions = "*"
+files = [
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+]
+
+[package.dependencies]
+numpy = ">=1.4"
+six = "*"
+
+[package.extras]
+test = ["pytest", "pytest-cov", "scipy"]
+
 [[package]]
 name = "peft"
 version = "0.11.1"
@@ -3631,6 +5049,26 @@ docs = ["furo (>=2023.9.10)", "proselint (>=0.13)", "sphinx (>=7.2.6)", "sphinx-
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 type = ["mypy (>=1.8)"]
 
+[[package]]
+name = "playwright"
+version = "1.46.0"
+description = "A high-level API to automate web browsers"
+optional = false
+python-versions = ">=3.8"
+files = [
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+]
+
+[package.dependencies]
+greenlet = "3.0.3"
+pyee = "11.1.0"
+
 [[package]]
 name = "pluggy"
 version = "1.5.0"
@@ -3686,6 +5124,52 @@ docs = ["sphinx (>=1.7.1)"]
 redis = ["redis"]
 tests = ["pytest (>=5.4.1)", "pytest-cov (>=2.8.1)", "pytest-mypy (>=0.8.0)", "pytest-timeout (>=2.1.0)", "redis", "sphinx (>=6.0.0)", "types-redis"]
 
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+version = "3.0.9"
+description = "Cython hash table that trusts the keys are pre-hashed"
+optional = false
+python-versions = ">=3.6"
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+murmurhash = ">=0.28.0,<1.1.0"
+
 [[package]]
 name = "prompt-toolkit"
 version = "3.0.47"
@@ -3864,6 +5348,47 @@ files = [
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 ]
 
+[[package]]
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+description = "Cryptographic library for Python"
+optional = false
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
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+
 [[package]]
 name = "pydantic"
 version = "2.8.2"
@@ -3992,12 +5517,29 @@ name = "pydub"
 version = "0.25.1"
 description = "Manipulate audio with an simple and easy high level interface"
 optional = false
-python-versions = "*"
+python-versions = "*"
+files = [
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+
+[[package]]
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+version = "11.1.0"
+description = "A rough port of Node.js's EventEmitter to Python with a few tricks of its own"
+optional = false
+python-versions = ">=3.8"
 files = [
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 ]
 
+[package.dependencies]
+typing-extensions = "*"
+
+[package.extras]
+dev = ["black", "build", "flake8", "flake8-black", "isort", "jupyter-console", "mkdocs", "mkdocs-include-markdown-plugin", "mkdocstrings[python]", "pytest", "pytest-asyncio", "pytest-trio", "sphinx", "toml", "tox", "trio", "trio", "trio-typing", "twine", "twisted", "validate-pyproject[all]"]
+
 [[package]]
 name = "pyflakes"
 version = "3.2.0"
@@ -4114,9 +5656,11 @@ files = [
 
 [package.dependencies]
 colorama = {version = "*", markers = "sys_platform == \"win32\""}
+exceptiongroup = {version = ">=1.0.0rc8", markers = "python_version < \"3.11\""}
 iniconfig = "*"
 packaging = "*"
 pluggy = ">=1.5,<2.0"
+tomli = {version = ">=1", markers = "python_version < \"3.11\""}
 
 [package.extras]
 dev = ["argcomplete", "attrs (>=19.2)", "hypothesis (>=3.56)", "mock", "pygments (>=2.7.2)", "requests", "setuptools", "xmlschema"]
@@ -4918,6 +6462,27 @@ dev = ["cython-lint (>=0.12.2)", "doit (>=0.36.0)", "mypy (==1.10.0)", "pycodest
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+[[package]]
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+description = "Statistical data visualization"
+optional = false
+python-versions = ">=3.8"
+files = [
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+numpy = ">=1.20,<1.24.0 || >1.24.0"
+pandas = ">=1.2"
+
+[package.extras]
+dev = ["flake8", "flit", "mypy", "pandas-stubs", "pre-commit", "pytest", "pytest-cov", "pytest-xdist"]
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+stats = ["scipy (>=1.7)", "statsmodels (>=0.12)"]
+
 [[package]]
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 version = "2.10.0"
@@ -5205,6 +6770,31 @@ files = [
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 ]
 
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+description = "Utils for streaming large files (S3, HDFS, GCS, Azure Blob Storage, gzip, bz2...)"
+optional = false
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+
+[package.extras]
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+azure = ["azure-common", "azure-core", "azure-storage-blob"]
+gcs = ["google-cloud-storage (>=2.6.0)"]
+http = ["requests"]
+s3 = ["boto3"]
+ssh = ["paramiko"]
+test = ["azure-common", "azure-core", "azure-storage-blob", "boto3", "google-cloud-storage (>=2.6.0)", "moto[server]", "paramiko", "pytest", "pytest-rerunfailures", "requests", "responses", "zstandard"]
+webhdfs = ["requests"]
+zst = ["zstandard"]
+
 [[package]]
 name = "smmap"
 version = "5.0.1"
@@ -5227,6 +6817,77 @@ files = [
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 ]
 
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+optional = false
+python-versions = ">=3.8"
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+
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+python-versions = "*"
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 [[package]]
 name = "sounddevice"
 version = "0.4.7"
@@ -5307,6 +6968,266 @@ numpy = "*"
 docs = ["linkify-it-py", "myst-parser", "sphinx", "sphinx-book-theme"]
 test = ["pytest"]
 
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 protobuf = ">=3.20"
 
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+tensorflow-rocm = ["tensorflow-rocm (>=2.16.0,<2.17.0)"]
+
 [[package]]
 name = "termcolor"
 version = "2.4.0"
@@ -5400,6 +7502,89 @@ files = [
 [package.extras]
 tests = ["pytest", "pytest-cov"]
 
+[[package]]
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+torch = ["torch (>=1.6.0)"]
+
 [[package]]
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 version = "3.5.0"
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+
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+requests = ">=2.26.0"
+
+[package.extras]
+blobfile = ["blobfile (>=2)"]
+
 [[package]]
 name = "tokenizers"
 version = "0.19.1"
@@ -5528,6 +7765,17 @@ dev = ["tokenizers[testing]"]
 docs = ["setuptools-rust", "sphinx", "sphinx-rtd-theme"]
 testing = ["black (==22.3)", "datasets", "numpy", "pytest", "requests", "ruff"]
 
+[[package]]
+name = "tomli"
+version = "2.0.1"
+description = "A lil' TOML parser"
+optional = false
+python-versions = ">=3.7"
+files = [
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+]
+
 [[package]]
 name = "tomlkit"
 version = "0.12.0"
@@ -5816,6 +8064,17 @@ files = [
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 ]
 
+[[package]]
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+version = "4.66.0.20240417"
+description = "Typing stubs for tqdm"
+optional = false
+python-versions = ">=3.8"
+files = [
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+]
+
 [[package]]
 name = "typing-extensions"
 version = "4.12.2"
@@ -5853,6 +8112,17 @@ files = [
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 ]
 
+[[package]]
+name = "uritemplate"
+version = "4.1.1"
+description = "Implementation of RFC 6570 URI Templates"
+optional = false
+python-versions = ">=3.6"
+files = [
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+]
+
 [[package]]
 name = "urllib3"
 version = "2.2.2"
@@ -5884,6 +8154,7 @@ files = [
 [package.dependencies]
 click = ">=7.0"
 h11 = ">=0.8"
+typing-extensions = {version = ">=4.0", markers = "python_version < \"3.11\""}
 
 [package.extras]
 standard = ["colorama (>=0.4)", "httptools (>=0.5.0)", "python-dotenv (>=0.13)", "pyyaml (>=5.1)", "uvloop (>=0.14.0,!=0.15.0,!=0.15.1)", "watchfiles (>=0.13)", "websockets (>=10.4)"]
@@ -5945,6 +8216,20 @@ perf = ["orjson"]
 sweeps = ["sweeps (>=0.2.0)"]
 workspaces = ["wandb-workspaces"]
 
+[[package]]
+name = "wasabi"
+version = "1.1.3"
+description = "A lightweight console printing and formatting toolkit"
+optional = false
+python-versions = ">=3.6"
+files = [
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+]
+
+[package.dependencies]
+colorama = {version = ">=0.4.6", markers = "sys_platform == \"win32\" and python_version >= \"3.7\""}
+
 [[package]]
 name = "wcwidth"
 version = "0.2.13"
@@ -5956,6 +8241,28 @@ files = [
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 ]
 
+[[package]]
+name = "weasel"
+version = "0.4.1"
+description = "Weasel: A small and easy workflow system"
+optional = false
+python-versions = ">=3.7"
+files = [
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+]
+
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+cloudpathlib = ">=0.7.0,<1.0.0"
+confection = ">=0.0.4,<0.2.0"
+packaging = ">=20.0"
+pydantic = ">=1.7.4,<1.8 || >1.8,<1.8.1 || >1.8.1,<3.0.0"
+requests = ">=2.13.0,<3.0.0"
+smart-open = ">=5.2.1,<8.0.0"
+srsly = ">=2.4.3,<3.0.0"
+typer = ">=0.3.0,<1.0.0"
+wasabi = ">=0.9.1,<1.2.0"
+
 [[package]]
 name = "websockets"
 version = "11.0.3"
@@ -6035,6 +8342,116 @@ files = [
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 ]
 
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+description = "The comprehensive WSGI web application library."
+optional = false
+python-versions = ">=3.8"
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+
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+MarkupSafe = ">=2.1.1"
+
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+watchdog = ["watchdog (>=2.3)"]
+
+[[package]]
+name = "wheel"
+version = "0.44.0"
+description = "A built-package format for Python"
+optional = false
+python-versions = ">=3.8"
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+    {file = "zstandard-0.23.0-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:fe3b385d996ee0822fd46528d9f0443b880d4d05528fd26a9119a54ec3f91c69"},
+    {file = "zstandard-0.23.0-cp39-cp39-musllinux_1_2_ppc64le.whl", hash = "sha256:82d17e94d735c99621bf8ebf9995f870a6b3e6d14543b99e201ae046dfe7de70"},
+    {file = "zstandard-0.23.0-cp39-cp39-musllinux_1_2_s390x.whl", hash = "sha256:c7c517d74bea1a6afd39aa612fa025e6b8011982a0897768a2f7c8ab4ebb78a2"},
+    {file = "zstandard-0.23.0-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:1fd7e0f1cfb70eb2f95a19b472ee7ad6d9a0a992ec0ae53286870c104ca939e5"},
+    {file = "zstandard-0.23.0-cp39-cp39-win32.whl", hash = "sha256:43da0f0092281bf501f9c5f6f3b4c975a8a0ea82de49ba3f7100e64d422a1274"},
+    {file = "zstandard-0.23.0-cp39-cp39-win_amd64.whl", hash = "sha256:f8346bfa098532bc1fb6c7ef06783e969d87a99dd1d2a5a18a892c1d7a643c58"},
+    {file = "zstandard-0.23.0.tar.gz", hash = "sha256:b2d8c62d08e7255f68f7a740bae85b3c9b8e5466baa9cbf7f57f1cde0ac6bc09"},
+]
+
+[package.dependencies]
+cffi = {version = ">=1.11", markers = "platform_python_implementation == \"PyPy\""}
+
+[package.extras]
+cffi = ["cffi (>=1.11)"]
+
 [[package]]
 name = "zstd"
 version = "1.5.5.1"
@@ -6353,5 +8882,5 @@ files = [
 
 [metadata]
 lock-version = "2.0"
-python-versions = "^3.11"
-content-hash = "3555084505e2e485a2f5ec2cdc7869e0369d7c2942bcd374a74dd08915a3daf3"
+python-versions = ">=3.10,<4.0"
+content-hash = "70cda1d7eb287a6cd00d2cf8a285c5f2613fcdea125caf03951258ecad79289c"
diff --git a/pyproject.toml b/pyproject.toml
index e0c473db..307f8a75 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -8,7 +8,7 @@ license = "MIT"
 readme = "README.md"
 
 [tool.poetry.dependencies]
-python = "^3.11"
+python = ">=3.10,<4.0"
 torch = ">=2.4"
 transformers = {version = ">=4.43.1", extras = ["torch"]}
 bitsandbytes = "~0.42.0"
@@ -29,6 +29,7 @@ tensorboardx = "~2.6.2.2"
 wandb = "~0.17.1"
 sacrebleu = "^2.4.2"
 tenacity = "^9.0.0"
+evals = {git = "https://github.com/fixie-ai/evals"}
 
 [tool.poetry.group.dev.dependencies]
 black = "~24.4.2"
diff --git a/setup.sh b/setup.sh
index 4cd89885..b6f95191 100644
--- a/setup.sh
+++ b/setup.sh
@@ -1,7 +1,7 @@
 cd $HOME
 mkdir workspace
 cd workspace
-git clone git@github.com:fixie-ai/ultravox.git -b main
+git clone https://github.com/fixie-ai/ultravox.git -b main
 cd ultravox
 mkdir -p ~/.local/bin
 curl --proto '=https' --tlsv1.2 -sSf https://just.systems/install.sh | bash -s -- --to ~/.local/bin
diff --git a/ultravox/model/ultravox_model.py b/ultravox/model/ultravox_model.py
index b01ac55b..cb209888 100644
--- a/ultravox/model/ultravox_model.py
+++ b/ultravox/model/ultravox_model.py
@@ -9,13 +9,13 @@
 import transformers.activations
 import transformers.modeling_outputs
 import transformers.models
+from transformers.models.whisper import modeling_whisper as whisper
 
 # We must use relative import in this directory to allow uploading to HF Hub
 # Even "from . import X" pattern doesn't work (undocumented and unclear why)
 from .ultravox_config import LossConfig
 from .ultravox_config import LossFunction
 from .ultravox_config import UltravoxConfig
-from .whisper_model_modified import WhisperEncoder as ModifiedWhisperEncoder
 
 
 class UltravoxModel(transformers.LlamaPreTrainedModel):
@@ -268,7 +268,7 @@ def prepare_inputs_for_generation(
     @classmethod
     def _create_audio_tower(
         cls, config: UltravoxConfig
-    ) -> Union[transformers.Wav2Vec2Model, ModifiedWhisperEncoder]:
+    ) -> Union[transformers.Wav2Vec2Model, "ModifiedWhisperEncoder"]:
         if config.audio_model_id is not None:
             if "whisper" in config.audio_model_id is not None:
                 audio_tower = ModifiedWhisperEncoder.from_pretrained(
@@ -496,6 +496,126 @@ def forward(self, audio_features: torch.Tensor) -> torch.Tensor:
         return hidden_states
 
 
+class ModifiedWhisperEncoder(whisper.WhisperEncoder):
+    """
+    Encoder portion of OpenAI's Whisper model.
+
+    This implementation is a slightly modified version of HF Transformers' Whisper Encoder, with only a few fixes:
+    1. base_model_prefix updated to allow for doing `.from_pretrained` directly on the encoder
+    2. allow less than 30 second of audio padding to be passed in:
+        - relaxed ValueError check for `input_features` length to be less than or equal to `expected_seq_length` instead of strictly equal
+        - embed_pos is now sliced to match the length of `inputs_embeds`
+
+    Original: https://github.com/huggingface/transformers/blob/main/src/transformers/models/whisper/modeling_whisper.py
+    """
+
+    base_model_prefix = "model.encoder"
+
+    def forward(
+        self,
+        input_features,
+        attention_mask=None,
+        head_mask=None,
+        output_attentions=None,
+        output_hidden_states=None,
+        return_dict=None,
+    ):
+        expected_seq_length = (
+            self.config.max_source_positions
+            * self.conv1.stride[0]
+            * self.conv2.stride[0]
+        )
+        if input_features.shape[-1] > expected_seq_length:
+            raise ValueError(
+                f"Whisper expects the mel input features to be of length {expected_seq_length} or less, but found {input_features.shape[-1]}. Make sure to pad the input mel features to {expected_seq_length}."
+            )
+
+        output_attentions = (
+            output_attentions
+            if output_attentions is not None
+            else self.config.output_attentions
+        )
+        output_hidden_states = (
+            output_hidden_states
+            if output_hidden_states is not None
+            else self.config.output_hidden_states
+        )
+        return_dict = (
+            return_dict if return_dict is not None else self.config.use_return_dict
+        )
+        inputs_embeds = nn.functional.gelu(self.conv1(input_features))
+        inputs_embeds = nn.functional.gelu(self.conv2(inputs_embeds))
+
+        inputs_embeds = inputs_embeds.permute(0, 2, 1)
+        embed_pos = self.embed_positions.weight[: inputs_embeds.size(-2)]
+
+        hidden_states = inputs_embeds + embed_pos
+        hidden_states = nn.functional.dropout(
+            hidden_states, p=self.dropout, training=self.training
+        )
+
+        encoder_states = () if output_hidden_states else None
+        all_attentions = () if output_attentions else None
+
+        # check if head_mask has a correct number of layers specified if desired
+        if head_mask is not None:
+            assert head_mask.size()[0] == (
+                len(self.layers)
+            ), f"The head_mask should be specified for {len(self.layers)} layers, but it is for {head_mask.size()[0]}."
+
+        for idx, encoder_layer in enumerate(self.layers):
+            if output_hidden_states:
+                encoder_states = encoder_states + (hidden_states,)
+            # add LayerDrop (see https://arxiv.org/abs/1909.11556 for description)
+            to_drop = False
+            if self.training:
+                dropout_probability = torch.rand([])
+                if dropout_probability < self.layerdrop:  # skip the layer
+                    to_drop = True
+
+            if to_drop:
+                layer_outputs = (None, None)
+            else:
+                if self.gradient_checkpointing and self.training:
+                    layer_outputs = self._gradient_checkpointing_func(
+                        encoder_layer.__call__,
+                        hidden_states,
+                        None,
+                        (head_mask[idx] if head_mask is not None else None),
+                        output_attentions,
+                    )
+                else:
+                    layer_outputs = encoder_layer(
+                        hidden_states,
+                        None,
+                        layer_head_mask=(
+                            head_mask[idx] if head_mask is not None else None
+                        ),
+                        output_attentions=output_attentions,
+                    )
+
+                hidden_states = layer_outputs[0]
+
+            if output_attentions:
+                all_attentions = all_attentions + (layer_outputs[1],)
+
+        hidden_states = self.layer_norm(hidden_states)
+        if output_hidden_states:
+            encoder_states = encoder_states + (hidden_states,)
+
+        if not return_dict:
+            return tuple(
+                v
+                for v in [hidden_states, encoder_states, all_attentions]
+                if v is not None
+            )
+        return transformers.modeling_outputs.BaseModelOutput(
+            last_hidden_state=hidden_states,
+            hidden_states=encoder_states,
+            attentions=all_attentions,
+        )
+
+
 UltravoxConfig.register_for_auto_class()
 UltravoxModel.register_for_auto_class()
 
diff --git a/ultravox/model/ultravox_processing.py b/ultravox/model/ultravox_processing.py
index fddb3b40..81bd34dd 100644
--- a/ultravox/model/ultravox_processing.py
+++ b/ultravox/model/ultravox_processing.py
@@ -56,6 +56,9 @@ def __init__(
         assert (
             self.audio_token_replacement is not None
         ), "The tokenizer has no EOS token. Cannot recover."
+        if tokenizer.pad_token_id is None:
+            tokenizer.pad_token_id = tokenizer.eos_token_id
+
         super().__init__(audio_processor=audio_processor, tokenizer=tokenizer)
 
     @classmethod
diff --git a/ultravox/model/whisper_model_modified.py b/ultravox/model/whisper_model_modified.py
deleted file mode 100644
index bf447f9b..00000000
--- a/ultravox/model/whisper_model_modified.py
+++ /dev/null
@@ -1,141 +0,0 @@
-# modified from https://github.com/huggingface/transformers/blob/main/src/transformers/models/whisper/modeling_whisper.py
-# see this issue for the commentary: https://github.com/huggingface/transformers/issues/25744
-#
-# Copyright 2022 The OpenAI Authors and The HuggingFace Inc. team. All rights reserved.
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-import torch
-import torch.nn as nn
-import transformers
-import transformers.modeling_outputs
-from transformers.models.whisper import modeling_whisper as whisper
-
-
-class WhisperEncoder(whisper.WhisperEncoder):
-    """
-    Encoder portion of OpenAI's Whisper model.
-
-    This implementation is a slightly modified version of HF Transformers' Whisper Encoder, with only a few fixes:
-    1. base_model_prefix updated to allow for doing `.from_pretrained` directly on the encoder
-    2. allow less than 30 second of audio padding to be passed in:
-        - relaxed ValueError check for `input_features` length to be less than or equal to `expected_seq_length` instead of strictly equal
-        - embed_pos is now sliced to match the length of `inputs_embeds`
-
-    Original: https://github.com/huggingface/transformers/blob/main/src/transformers/models/whisper/modeling_whisper.py
-    """
-
-    base_model_prefix = "model.encoder"
-
-    def forward(
-        self,
-        input_features,
-        attention_mask=None,
-        head_mask=None,
-        output_attentions=None,
-        output_hidden_states=None,
-        return_dict=None,
-    ):
-        expected_seq_length = (
-            self.config.max_source_positions
-            * self.conv1.stride[0]
-            * self.conv2.stride[0]
-        )
-        if input_features.shape[-1] > expected_seq_length:
-            raise ValueError(
-                f"Whisper expects the mel input features to be of length {expected_seq_length} or less, but found {input_features.shape[-1]}. Make sure to pad the input mel features to {expected_seq_length}."
-            )
-
-        output_attentions = (
-            output_attentions
-            if output_attentions is not None
-            else self.config.output_attentions
-        )
-        output_hidden_states = (
-            output_hidden_states
-            if output_hidden_states is not None
-            else self.config.output_hidden_states
-        )
-        return_dict = (
-            return_dict if return_dict is not None else self.config.use_return_dict
-        )
-        inputs_embeds = nn.functional.gelu(self.conv1(input_features))
-        inputs_embeds = nn.functional.gelu(self.conv2(inputs_embeds))
-
-        inputs_embeds = inputs_embeds.permute(0, 2, 1)
-        embed_pos = self.embed_positions.weight[: inputs_embeds.size(-2)]
-
-        hidden_states = inputs_embeds + embed_pos
-        hidden_states = nn.functional.dropout(
-            hidden_states, p=self.dropout, training=self.training
-        )
-
-        encoder_states = () if output_hidden_states else None
-        all_attentions = () if output_attentions else None
-
-        # check if head_mask has a correct number of layers specified if desired
-        if head_mask is not None:
-            assert head_mask.size()[0] == (
-                len(self.layers)
-            ), f"The head_mask should be specified for {len(self.layers)} layers, but it is for {head_mask.size()[0]}."
-
-        for idx, encoder_layer in enumerate(self.layers):
-            if output_hidden_states:
-                encoder_states = encoder_states + (hidden_states,)
-            # add LayerDrop (see https://arxiv.org/abs/1909.11556 for description)
-            to_drop = False
-            if self.training:
-                dropout_probability = torch.rand([])
-                if dropout_probability < self.layerdrop:  # skip the layer
-                    to_drop = True
-
-            if to_drop:
-                layer_outputs = (None, None)
-            else:
-                if self.gradient_checkpointing and self.training:
-                    layer_outputs = self._gradient_checkpointing_func(
-                        encoder_layer.__call__,
-                        hidden_states,
-                        None,
-                        (head_mask[idx] if head_mask is not None else None),
-                        output_attentions,
-                    )
-                else:
-                    layer_outputs = encoder_layer(
-                        hidden_states,
-                        None,
-                        layer_head_mask=(
-                            head_mask[idx] if head_mask is not None else None
-                        ),
-                        output_attentions=output_attentions,
-                    )
-
-                hidden_states = layer_outputs[0]
-
-            if output_attentions:
-                all_attentions = all_attentions + (layer_outputs[1],)
-
-        hidden_states = self.layer_norm(hidden_states)
-        if output_hidden_states:
-            encoder_states = encoder_states + (hidden_states,)
-
-        if not return_dict:
-            return tuple(
-                v
-                for v in [hidden_states, encoder_states, all_attentions]
-                if v is not None
-            )
-        return transformers.modeling_outputs.BaseModelOutput(
-            last_hidden_state=hidden_states,
-            hidden_states=encoder_states,
-            attentions=all_attentions,
-        )
diff --git a/ultravox/training/config_base.py b/ultravox/training/config_base.py
index 182887a9..232c0584 100644
--- a/ultravox/training/config_base.py
+++ b/ultravox/training/config_base.py
@@ -43,6 +43,7 @@ class TrainConfig:
     eval_num_samples: int = 100
     eval_max_new_tokens: Optional[int] = None
     eval_num_procs: int = 8
+    eval_text_only: bool = False
     num_prompts: int = 1
     # number of data loader workers
     num_workers: int = 8 if torch.cuda.is_available() else 1
diff --git a/ultravox/training/configs/meta_config.yaml b/ultravox/training/configs/meta_config.yaml
index 9ccb4348..dd71828d 100644
--- a/ultravox/training/configs/meta_config.yaml
+++ b/ultravox/training/configs/meta_config.yaml
@@ -11,7 +11,7 @@ max_audio_duration_secs: 16
 
 val_num_samples: 64
 val_steps: 1000
-eval_num_samples: 256
+eval_num_samples: 1024
 eval_max_new_tokens: 32
 eval_num_procs: 16
 
diff --git a/ultravox/training/train.py b/ultravox/training/train.py
index f4b590c6..bba3c33b 100644
--- a/ultravox/training/train.py
+++ b/ultravox/training/train.py
@@ -1,14 +1,17 @@
 import copy
 import dataclasses
+import gc
 import glob
 import logging
 import os
 import re
+import subprocess
 import sys
 from datetime import datetime
 from typing import Dict, List, Optional
 
 import datasets as hf_datasets
+import pandas as pd
 import safetensors.torch
 import simple_parsing
 import torch
@@ -16,19 +19,17 @@
 import transformers
 import wandb
 import wandb.sdk
-from torch.distributed.elastic.multiprocessing.errors import record
 from torch.utils import data
 
 from ultravox.data import datasets
-from ultravox.inference import infer
 from ultravox.model import data_processing
 from ultravox.model import ultravox_config
 from ultravox.model import ultravox_model
+from ultravox.model import ultravox_pipeline
 from ultravox.model import ultravox_processing
 from ultravox.model import wandb_utils
 from ultravox.training import config_base
 from ultravox.training import ddp_utils
-from ultravox.training import evaluation
 
 INPUT_EXAMPLE = {"text": "Transcribe\n<|audio|>", "audio": b"\x00\x00" * 16000}
 OUTPUT_EXAMPLE = {"text": "Hello, world!"}
@@ -60,7 +61,6 @@ def prepare_dataset(
     return limited_ds
 
 
-@record
 def main() -> None:
     # Disable parallelism to avoid deadlocks in DataLoader, apparently
     # multiple processes are forked when using multiple datasets.
@@ -78,6 +78,19 @@ def main() -> None:
 
     transformers.set_seed(args.seed)
 
+    local_rank = int(os.environ.get("LOCAL_RANK", 0))
+    is_master = local_rank == 0
+
+    if args.do_train:
+        train(args)
+
+    if args.do_eval and is_master:
+        gc.collect()
+        torch.cuda.empty_cache()
+        evaluate(args)
+
+
+def train(args: config_base.TrainConfig):
     world_size = int(os.environ.get("WORLD_SIZE", 1))
     local_rank = int(os.environ.get("LOCAL_RANK", 0))
     is_master = local_rank == 0
@@ -282,50 +295,112 @@ def main() -> None:
             # fsdp_transformer_layer_cls_to_wrap='LlamaDecoderLayer',
         ),
     )
-    if args.do_train:
-        # Training loop
-        logging.info("Starting training...")
-        t_start = datetime.now()
-        logging.info(f"train start time: {t_start}")
-        if args.val_steps:
-            trainer.evaluate()
-        trainer.train()
-        trainer.save_model(args.output_dir)
-        t_end = datetime.now()
-        logging.info(f"train end time: {t_end}")
-        logging.info(f"elapsed: {t_end - t_start}")
-
-    if args.do_eval:
-        logging.info("Starting evaluation...")
-        t_start = datetime.now()
-        logging.info(f"eval start time: {t_start}")
-
-        # Merge LoRA weights for better inference performance.
-        # Note: this is irreversible and changes model saving format
-        model.merge_and_unload()
-        # padding_side="left" is required for (batch) inference
-        text_tokenizer.padding_side = "left"
-        inference = infer.LocalInference(
-            model=model,
-            processor=processor,
-            tokenizer=text_tokenizer,
-            device=args.device,
-            dtype=dtype,
+
+    # Training loop
+    logging.info("Starting training...")
+    t_start = datetime.now()
+    logging.info(f"train start time: {t_start}")
+    if args.val_steps:
+        trainer.evaluate()
+    trainer.train()
+    if is_master:
+        # Saving the model using pipeline to ensure its code is saved
+        pipeline = ultravox_pipeline.UltravoxPipeline(
+            model, tokenizer=text_tokenizer, device=device
         )
-        metrics = evaluation.evaluate(
-            inference,
-            data_dir=args.data_dir,
-            num_procs=args.eval_num_procs,
+        pipeline.save_pretrained(args.output_dir)
+    t_end = datetime.now()
+    logging.info(f"train end time: {t_end}")
+    logging.info(f"elapsed: {t_end - t_start}")
+
+
+def evaluate(args: config_base.TrainConfig):
+    """
+    Evaluate the model on the audio and text datasets.
+
+    NOTE: This function must be run only on the primary process.
+    """
+    logging.info("Starting evaluation...")
+    t_start = datetime.now()
+    logging.info(f"eval start time: {t_start}")
+
+    if args.text_model_lora_config and args.text_model_lora_config.r:
+        logging.warn(
+            "Model has unmerged LoRA config. This can lead to slower inference."
+        )
+
+    logs_dir = wandb.run.dir if wandb.run else str(args.logs_dir)
+
+    # Run audio-based evaluations and log to W&B
+    audio_metrics_df = run_oaievalset(
+        log_dir=os.path.join(logs_dir, "oaieval/audio"),
+        model_dir=str(args.output_dir),
+        eval_set="audio-core",
+        num_samples=args.eval_num_samples,
+    )
+    # TODO: it would be best to do trainer.log, but then we'd risk keeping parts of the model
+    # in GPU memory, which could cause OOM errors.
+    if wandb.run:
+        wandb.run.log({"eval_audio": wandb.Table(data=audio_metrics_df)})
+
+    if args.eval_text_only:
+        # Run text-only evaluations and log to W&B
+        text_metrics_df = run_oaievalset(
+            log_dir=os.path.join(logs_dir, "oaieval/text"),
+            model_dir=str(args.output_dir),
+            eval_set="transcript-core",
             num_samples=args.eval_num_samples,
-            max_new_tokens=args.eval_max_new_tokens,
-            log_dir=wandb.run.dir if wandb.run else str(args.logs_dir),
         )
-        if is_master:
-            trainer.log(metrics)
+        if wandb.run:
+            wandb.run.log({"eval_text": wandb.Table(data=text_metrics_df)})
+
+    t_end = datetime.now()
+    logging.info(f"eval end time: {t_end}")
+    logging.info(f"elapsed: {t_end - t_start}")
+
+
+def run_oaievalset(
+    log_dir: str, model_dir: str, eval_set: str, num_samples: Optional[int] = None
+) -> pd.DataFrame:
+    env = os.environ.copy()
+
+    # num_gpus = max(1, torch.cuda.device_count())
+    env["EVALS_THREADS"] = "64"
+
+    # TODO: currently running this on a single GPU is faster than multiple GPUs :facepalm:
+    env["CUDA_VISIBLE_DEVICES"] = "0"
+
+    command = [
+        "oaievalset",
+        "--record_dir",
+        log_dir,
+        "generation/gpu/ultravox-dev",
+        eval_set,
+        f"--completion_args=model={model_dir}",
+    ]
+    if num_samples:
+        command.append(f"--max_samples={num_samples}")
+
+    # Run the evaluation set
+    subprocess.run(command, check=True, env=env)
+
+    # Extract the results from the log directory
+    subprocess.run(
+        [
+            "python",
+            "-m",
+            "evals.elsuite.audio.make_table",
+            "--out_dir",
+            log_dir,
+            "--log_dir",
+            log_dir,
+        ],
+        check=True,
+    )
+
+    df = pd.read_csv(os.path.join(log_dir, "results.csv"))
 
-        t_end = datetime.now()
-        logging.info(f"eval end time: {t_end}")
-        logging.info(f"elapsed: {t_end - t_start}")
+    return df
 
 
 if __name__ == "__main__":