🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
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Updated
Jul 6, 2024 - Python
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
A flexible package for multimodal-deep-learning to combine tabular data with text and images using Wide and Deep models in Pytorch
Minimalist NMT for educational purposes
Automatically split your PyTorch models on multiple GPUs for training & inference
HugsVision is a easy to use huggingface wrapper for state-of-the-art computer vision
A little Python application to auto tag your photos with the power of machine learning.
Label data using HuggingFace's transformers and automatically get a prediction service
When Paint meets Artificial Intelligence! A Python application to generate pictures based on your drawing.
Instructions for how to convert a BERT Tensorflow model to work with HuggingFace's pytorch-transformers, and spaCy. This walk-through uses DeepPavlov's RuBERT as example.
State-of-the-art NLP through transformer models in a modular design and consistent APIs.
A bunch of Python scripts to create a Pokémon Classifier.
A little Python application to generate pictures from a text prompt. Based on Stable Diffusion.
A little Pokédex application that can find a Pokémon in any image with the power of machine learning.
Source code for "LIMIT-BERT : Linguistics Informed Multi-Task BERT" published at Findings of EMNLP 2020
💁 Awesome Treasure of Transformers Models for Natural Language processing contains papers, videos, blogs, official repo along with colab Notebooks. 🛫☑️
Forecasting open-high-low-close (OHLC) data with Transformer models
Minimal implementation of Decision Transformer: Reinforcement Learning via Sequence Modeling in PyTorch for mujoco control tasks in OpenAI gym
Utilizing webscraping and state-of-the-art NLP to generate TV show episode summaries.
医药知识图谱自动问答系统实现,包括构建知识图谱、基于知识图谱的流水线问答以及前端实现。实体识别(基于词典+BERT_CRF)、实体链接(Sentence-BERT做匹配)、意图识别(基于提问词+领域词词典)。
A better PyTorch data loader capable of custom image operations and image subsets
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