Hugging Face Transformers: BART, organizations, community notebooks, lightning examples, dropping Python 3.5
Hugging Face Transformers v2.6.0. Source highlight: New Model: BART (added by @sshleifer)
AI Models & LLM Frameworks archive — Page 25
1224 tracked entries. Older history is imported progressively; see source coverage.
Hugging Face Transformers: Patch v2.5.1: AutoTokenizer slow by default, bug fixes
Hugging Face Transformers v2.5.1. Source highlight: AutoTokenizer has been put back to False by default so as to not have a breaking change between 2.4.x and 2.5.x
Hugging Face Transformers: Rust Tokenizers, DistilBERT base cased, Model cards
Hugging Face Transformers v2.5.0. Source highlight: Rust tokenizers (@mfuntowicz, @n1t0 )
Hugging Face Transformers: Patch v2.4.1: FlauBERT for AutoModel and AutoTokenizer
Hugging Face Transformers v2.4.1 is published, but the available notes are too limited to assess upgrade impact. Review the official source before upgrading.
Hugging Face Transformers: FlauBERT, MMBT, UmBERTo, Dutch model, improved documentation, training from scratch, clean Python code
Hugging Face Transformers v2.4.0. Source highlight: FlauBERT, MMBT, UmBERTo
Hugging Face Transformers: Downstream NLP task API (feature extraction, text classification, NER, QA), Command-Line Interface and Serving – models: T5 – community-added models: Japanese & Finnish BERT, PPLM, XLM-R
Hugging Face Transformers v2.3.0. Source highlight: New class `Pipeline` (beta): easily run and use models on down-stream NLP tasks
Hugging Face Transformers: Bug fixes
Hugging Face Transformers v2.2.2 is published, but the available notes are too limited to assess upgrade impact. Review the official source before upgrading.
Hugging Face Transformers: Bug fixes related to input shape in TensorFlow and tokenization messages
Hugging Face Transformers v2.2.1. Source highlight: This patch fixes a bug related to the input shape in several models in TensorFlow.
Hugging Face Transformers: ALBERT, CamemBERT, DistilRoberta, GPT-2 XL, and Encoder-Decoder architectures
Hugging Face Transformers v2.2.0. Source highlight: New model architectures: ALBERT, CamemBERT, GPT2-XL, DistilRoberta
Hugging Face Transformers: CTRL, DistilGPT-2, Pytorch TPU, tokenizer enhancements, guideline requirements
Hugging Face Transformers v2.1.1. Source highlight: New model architectures: CTRL, DistilGPT-2
Hugging Face Transformers: Superseded by v2.1.1
Hugging Face Transformers v2.1.0 is published, but the available notes are too limited to assess upgrade impact. Review the official source before upgrading.
Hugging Face Transformers: v2.0.0 - TF 2.0/PyTorch interoperability, improved tokenizers, improved torchscript support
Hugging Face Transformers v2.0.0. Source highlight: Name change: welcome 🤗 Transformers
Hugging Face Transformers: DistilBERT, GPT-2 Large, XLM multilingual models, torch.hub, bug fixes
Hugging Face Transformers 1.2.0. Source highlight: New model architecture: DistilBERT
Hugging Face Transformers: New model: RoBERTa, tokenizer sequence pair handling for sequence classification models.
Hugging Face Transformers 1.1.0. Source highlight: **RoBERTa** (from Facebook), a Robustly Optimized BERT Pretraining Approach by Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du et al.
Hugging Face Transformers: v1.0.0 - Name change, new models (XLNet, XLM), unified API for models and tokenizer, access to models internals, torchscript
Hugging Face Transformers v1.0.0. Source highlight: Name change: welcome PyTorch-Transformers 👾
Hugging Face Transformers: Better model/tokenizer serialization, relax network connection requirements, new scripts and bug fixes
Hugging Face Transformers v0.6.2. Source highlight: Better serialization for all models and tokenizers (BERT, GPT, GPT-2 and Transformer-XL) with best practices for saving/loading in readme and examples.
Hugging Face Transformers: v0.6.1 - Small install tweak release
Hugging Face Transformers v0.6.1 is published, but the available notes are too limited to assess upgrade impact. Review the official source before upgrading.
Hugging Face Transformers: v0.6.0 - Adding OpenAI small GPT-2 pretrained model
Hugging Face Transformers v0.6.0 is published, but the available notes are too limited to assess upgrade impact. Review the official source before upgrading.
Hugging Face Transformers: Bug fix update to load the pretrained `TransfoXLModel` from s3, added fallback for OpenAIGPTTokenizer when SpaCy is not installed
Hugging Face Transformers v0.5.1. Source highlight: Mostly a bug fix update for loading the `TransfoXLModel` from s3:
Hugging Face Transformers: Adding OpenAI GPT and Transformer-XL pretrained models, python2 support, pre-training script for BERT, SQuAD 2.0 example
Hugging Face Transformers v0.5.0. Source highlight: New pretrained models:
Hugging Face Transformers: 4x speed-up using NVIDIA apex, new multi-choice classifier and example for SWAG-like dataset, pytorch v1.0, improved model loading, improved examples...
Hugging Face Transformers v0.4.0. Source highlight: 3-4 times speed-ups in fp16 (versus fp32) thanks to NVIDIA's work on apex (by @FDecaYed)
Hugging Face Transformers: Added two pre-trained models and one new fine-tuning class
Hugging Face Transformers v0.3.0. Source highlight: This release comprise the following improvements and updates:
Hugging Face Transformers: Small improvements and a few bug fixes.
Hugging Face Transformers v0.2.0. Source highlight: Added a `cache_dir` option to `from_pretrained()` function to select a specific path to download and cache the pre-trained model weights. Useful for distributed training (see readme) (fix issue #44).
Hugging Face Transformers: First release
Hugging Face Transformers v0.1.2 is published, but the available notes are too limited to assess upgrade impact. Review the official source before upgrading.