• Stars
    star
    1,464
  • Rank 30,755 (Top 0.7 %)
  • Language
    Python
  • License
    MIT License
  • Created almost 6 years ago
  • Updated over 2 years ago

Reviews

There are no reviews yet. Be the first to send feedback to the community and the maintainers!

Repository Details

πŸ₯A PyTorch implementation of OpenAI's finetuned transformer language model with a script to import the weights pre-trained by OpenAI

PyTorch implementation of OpenAI's Finetuned Transformer Language Model

This is a PyTorch implementation of the TensorFlow code provided with OpenAI's paper "Improving Language Understanding by Generative Pre-Training" by Alec Radford, Karthik Narasimhan, Tim Salimans and Ilya Sutskever.

This implementation comprises a script to load in the PyTorch model the weights pre-trained by the authors with the TensorFlow implementation.

Transformer Language Model

The model classes and loading script are located in model_pytorch.py.

The names of the modules in the PyTorch model follow the names of the Variable in the TensorFlow implementation. This implementation tries to follow the original code as closely as possible to minimize the discrepancies.

This implementation thus also comprises a modified Adam optimization algorithm as used in OpenAI's paper with:

Requirements

To use the model it-self by importing model_pytorch.py, you just need:

  • PyTorch (version >=0.4)

To run the classifier training script in train.py you will need in addition:

  • tqdm
  • sklearn
  • spacy
  • ftfy
  • pandas

You can download the weights of the OpenAI pre-trained version by cloning Alec Radford's repo and placing the model folder containing the pre-trained weights in the present repo.

Using the pre-trained model as a Transformer Language Model

The model can be used as a transformer language model with OpenAI's pre-trained weights as follow:

from model_pytorch import TransformerModel, load_openai_pretrained_model, DEFAULT_CONFIG

args = DEFAULT_CONFIG
model = TransformerModel(args)
load_openai_pretrained_model(model)

This model generates Transformer's hidden states. You can use the LMHead class in model_pytorch.py to add a decoder tied with the weights of the encoder and get a full language model. You can also use the ClfHead class in model_pytorch.py to add a classifier on top of the transformer and get a classifier as described in OpenAI's publication. (see an example of both in the __main__ function of train.py)

To use the positional encoder of the transformer, you should encode your dataset using the encode_dataset() function of utils.py. Please refer to the beginning of the __main__ function in train.py to see how to properly define the vocabulary and encode your dataset.

Fine-tuning the pre-trained model on a classification task

This model can also be integrated in a classifier as detailed in OpenAI's paper. An example of fine-tuning on the ROCStories Cloze task is included with the training code in train.py

The ROCStories dataset can be downloaded from the associated website.

As with the TensorFlow code, this code implements the ROCStories Cloze Test result reported in the paper which can be reproduced by running:

python -m spacy download en
python train.py --dataset rocstories --desc rocstories --submit --analysis --data_dir [path to data here]

First experiments on the ROCStories test set

Finetuning the PyTorch model for 3 Epochs on ROCStories takes 10 minutes to run on a single NVidia K-80.

The single run test accuracy of this PyTorch version is 85.84%, while the authors reports a median accuracy with the TensorFlow code of 85.8% and the paper reports a best single run accuracy of 86.5%.

The authors implementations uses 8 GPU and can thus accomodate a batch of 64 samples while the present implementation is single GPU and is in consequence limited to 20 instances on a K80 for memory reasons. In our test, increasing the batch size from 8 to 20 samples increased the test accuracy by 2.5 points. A better accuracy may be obtained by using a multi-GPU setting (not tried yet).

The previous SOTA on the ROCStories dataset is 77.6% ("Hidden Coherence Model" of Chaturvedi et al. published in "Story Comprehension for Predicting What Happens Next" EMNLP 2017, which is a very nice paper too!)

More Repositories

1

transformers

πŸ€— Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
Python
121,026
star
2

pytorch-image-models

PyTorch image models, scripts, pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNet-V3/V2, RegNet, DPN, CSPNet, Swin Transformer, MaxViT, CoAtNet, ConvNeXt, and more
Python
28,073
star
3

diffusers

πŸ€— Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch
Python
21,823
star
4

datasets

πŸ€— The largest hub of ready-to-use datasets for ML models with fast, easy-to-use and efficient data manipulation tools
Python
17,530
star
5

peft

πŸ€— PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.
Python
13,148
star
6

candle

Minimalist ML framework for Rust
Rust
12,686
star
7

tokenizers

πŸ’₯ Fast State-of-the-Art Tokenizers optimized for Research and Production
Rust
8,286
star
8

trl

Train transformer language models with reinforcement learning.
Python
7,661
star
9

text-generation-inference

Large Language Model Text Generation Inference
Python
7,240
star
10

accelerate

πŸš€ A simple way to launch, train, and use PyTorch models on almost any device and distributed configuration, automatic mixed precision (including fp8), and easy-to-configure FSDP and DeepSpeed support
Python
6,878
star
11

chat-ui

Open source codebase powering the HuggingChat app
TypeScript
5,586
star
12

deep-rl-class

This repo contains the syllabus of the Hugging Face Deep Reinforcement Learning Course.
MDX
3,541
star
13

alignment-handbook

Robust recipes to align language models with human and AI preferences
Python
3,485
star
14

diffusion-models-class

Materials for the Hugging Face Diffusion Models Course
Jupyter Notebook
3,126
star
15

notebooks

Notebooks using the Hugging Face libraries πŸ€—
Jupyter Notebook
3,114
star
16

distil-whisper

Distilled variant of Whisper for speech recognition. 6x faster, 50% smaller, within 1% word error rate.
Python
2,964
star
17

neuralcoref

✨Fast Coreference Resolution in spaCy with Neural Networks
C
2,788
star
18

autotrain-advanced

πŸ€— AutoTrain Advanced
Python
2,759
star
19

knockknock

πŸšͺ✊Knock Knock: Get notified when your training ends with only two additional lines of code
Python
2,660
star
20

safetensors

Simple, safe way to store and distribute tensors
Python
2,347
star
21

swift-coreml-diffusers

Swift app demonstrating Core ML Stable Diffusion
Swift
2,329
star
22

optimum

πŸš€ Accelerate training and inference of πŸ€— Transformers and πŸ€— Diffusers with easy to use hardware optimization tools
Python
2,086
star
23

awesome-papers

Papers & presentation materials from Hugging Face's internal science day
1,996
star
24

setfit

Efficient few-shot learning with Sentence Transformers
Jupyter Notebook
1,912
star
25

text-embeddings-inference

A blazing fast inference solution for text embeddings models
Rust
1,845
star
26

course

The Hugging Face course on Transformers
MDX
1,832
star
27

evaluate

πŸ€— Evaluate: A library for easily evaluating machine learning models and datasets.
Python
1,752
star
28

blog

Public repo for HF blog posts
Jupyter Notebook
1,685
star
29

transfer-learning-conv-ai

πŸ¦„ State-of-the-Art Conversational AI with Transfer Learning
Python
1,654
star
30

swift-coreml-transformers

Swift Core ML 3 implementations of GPT-2, DistilGPT-2, BERT, and DistilBERT for Question answering. Other Transformers coming soon!
Swift
1,543
star
31

huggingface_hub

All the open source things related to the Hugging Face Hub.
Python
1,311
star
32

Mongoku

πŸ”₯The Web-scale GUI for MongoDB
TypeScript
1,277
star
33

hmtl

🌊HMTL: Hierarchical Multi-Task Learning - A State-of-the-Art neural network model for several NLP tasks based on PyTorch and AllenNLP
Python
1,181
star
34

huggingface.js

Utilities to use the Hugging Face Hub API
TypeScript
1,161
star
35

gsplat.js

JavaScript Gaussian Splatting library.
TypeScript
1,114
star
36

llm-vscode

LLM powered development for VSCode
TypeScript
1,060
star
37

datatrove

Freeing data processing from scripting madness by providing a set of platform-agnostic customizable pipeline processing blocks.
Python
1,033
star
38

pytorch-pretrained-BigGAN

πŸ¦‹A PyTorch implementation of BigGAN with pretrained weights and conversion scripts.
Python
986
star
39

torchMoji

πŸ˜‡A pyTorch implementation of the DeepMoji model: state-of-the-art deep learning model for analyzing sentiment, emotion, sarcasm etc
Python
880
star
40

naacl_transfer_learning_tutorial

Repository of code for the tutorial on Transfer Learning in NLP held at NAACL 2019 in Minneapolis, MN, USA
Python
717
star
41

awesome-huggingface

πŸ€— A list of wonderful open-source projects & applications integrated with Hugging Face libraries.
698
star
42

optimum-nvidia

Python
680
star
43

nanotron

Minimalistic large language model 3D-parallelism training
Python
661
star
44

datasets-server

Lightweight web API for visualizing and exploring all types of datasets - computer vision, speech, text, and tabular - stored on the Hugging Face Hub
Python
594
star
45

transformers-bloom-inference

Fast Inference Solutions for BLOOM
Python
546
star
46

pytorch_block_sparse

Fast Block Sparse Matrices for Pytorch
C++
523
star
47

exporters

Export Hugging Face models to Core ML and TensorFlow Lite
Python
518
star
48

llm.nvim

LLM powered development for Neovim
Lua
507
star
49

cookbook

Open-source AI cookbook
Jupyter Notebook
471
star
50

node-question-answering

Fast and production-ready question answering in Node.js
TypeScript
459
star
51

swift-transformers

Swift Package to implement a transformers-like API in Swift
Swift
438
star
52

large_language_model_training_playbook

An open collection of implementation tips, tricks and resources for training large language models
Python
431
star
53

llm-ls

LSP server leveraging LLMs for code completion (and more?)
Rust
416
star
54

llm_training_handbook

An open collection of methodologies to help with successful training of large language models.
Python
385
star
55

tflite-android-transformers

DistilBERT / GPT-2 for on-device inference thanks to TensorFlow Lite with Android demo apps
Java
368
star
56

community-events

Place where folks can contribute to πŸ€— community events
Jupyter Notebook
368
star
57

nn_pruning

Prune a model while finetuning or training.
Jupyter Notebook
360
star
58

swift-chat

Mac app to demonstrate swift-transformers
Swift
346
star
59

speechbox

Python
328
star
60

100-times-faster-nlp

πŸš€100 Times Faster Natural Language Processing in Python - iPython notebook
HTML
325
star
61

education-toolkit

Educational materials for universities
Jupyter Notebook
307
star
62

optimum-intel

πŸ€— Optimum Intel: Accelerate inference with Intel optimization tools
Jupyter Notebook
295
star
63

controlnet_aux

Python
291
star
64

unity-api

C#
284
star
65

open-muse

Open reproduction of MUSE for fast text2image generation.
Python
284
star
66

datablations

Scaling Data-Constrained Language Models
Jupyter Notebook
270
star
67

audio-transformers-course

The Hugging Face Course on Transformers for Audio
MDX
247
star
68

hub-docs

Docs of the Hugging Face Hub
221
star
69

text-clustering

Easily embed, cluster and semantically label text datasets
Python
214
star
70

lighteval

LightEval is a lightweight LLM evaluation suite that Hugging Face has been using internally with the recently released LLM data processing library datatrove and LLM training library nanotron.
Python
208
star
71

quanto

A pytorch Quantization Toolkit
Python
201
star
72

simulate

🎒 Creating and sharing simulation environments for embodied and synthetic data research
Python
185
star
73

ratchet

A cross-platform browser ML framework.
Rust
184
star
74

hf_transfer

Rust
181
star
75

instruction-tuned-sd

Code for instruction-tuning Stable Diffusion.
Python
167
star
76

olm-datasets

Pipeline for pulling and processing online language model pretraining data from the web
Python
166
star
77

optimum-neuron

Easy, fast and very cheap training and inference on AWS Trainium and Inferentia chips.
Jupyter Notebook
163
star
78

optimum-benchmark

A unified multi-backend utility for benchmarking Transformers and Diffusers with full support of Optimum's hardware optimizations & quantization schemes.
Python
163
star
79

workshops

Materials for workshops on the Hugging Face ecosystem
Jupyter Notebook
143
star
80

OBELICS

Code used for the creation of OBELICS, an open, massive and curated collection of interleaved image-text web documents, containing 141M documents, 115B text tokens and 353M images.
Python
142
star
81

cosmopedia

Python
138
star
82

api-inference-community

Python
131
star
83

diffusion-fast

Faster generation with text-to-image diffusion models.
Python
127
star
84

sharp-transformers

A Unity plugin for using Transformers models in Unity.
C#
104
star
85

llm-swarm

Manage scalable open LLM inference endpoints in Slurm clusters
Python
104
star
86

competitions

Python
98
star
87

optimum-habana

Easy and lightning fast training of πŸ€— Transformers on Habana Gaudi processor (HPU)
Python
98
star
88

hf-hub

Rust client for the huggingface hub aiming for minimal subset of features over `huggingface-hub` python package
Rust
93
star
89

olm-training

Repo for training MLMs, CLMs, or T5-type models on the OLM pretraining data, but it should work with any hugging face text dataset.
Python
87
star
90

fuego

[WIP] A πŸ”₯ interface for running code in the cloud
Python
84
star
91

tune

Python
83
star
92

datasets-viewer

Viewer for the πŸ€— datasets library.
Python
82
star
93

optimum-graphcore

Blazing fast training of πŸ€— Transformers on Graphcore IPUs
Python
78
star
94

frp

FRP Fork
Go
73
star
95

paper-style-guide

71
star
96

block_movement_pruning

Block Sparse movement pruning
Python
70
star
97

data-measurements-tool

Developing tools to automatically analyze datasets
Python
69
star
98

amused

Python
68
star
99

doc-builder

The package used to build the documentation of our Hugging Face repos
Python
67
star
100

hfapi

Simple Python client for the Hugging Face Inference API
Python
66
star