Hugging Face Transformers: v4.12.0: TrOCR, SEW & SEW-D, Unispeech & Unispeech-SAT, BARTPho
Hugging Face Transformers v4.12.0. Source highlight: TrOCR and VisionEncoderDecoderModel
AI Models & LLM Frameworks archive — Page 23
1172 tracked entries. Older history is imported progressively; see source coverage.
Hugging Face Transformers: v4.11.3: Patch release
Hugging Face Transformers v4.11.3. Source highlight: v4.11.3: Patch release
Hugging Face Transformers: v4.11.2: Patch release
Hugging Face Transformers v4.11.2 is published, but the available notes are too limited to assess upgrade impact. Review the official source before upgrading.
Hugging Face Transformers: v4.11.1: Patch release
Hugging Face Transformers v4.11.1. Source highlight: v4.11.1: Patch release
Hugging Face Transformers: v4.11.0: GPT-J, Speech2Text2, FNet, Pipeline GPU utilization, dynamic model code loading
Hugging Face Transformers v4.11.0. Source highlight: v4.11.0: GPT-J, Speech2Text2, FNet, Pipeline GPU utilization, dynamic model code loading
Hugging Face Transformers: v4.10.3: Patch release
Hugging Face Transformers v4.10.3 is published, but the available notes are too limited to assess upgrade impact. Review the official source before upgrading.
Hugging Face Transformers: v4.10.2: Patch release
Hugging Face Transformers v4.10.2 is published, but the available notes are too limited to assess upgrade impact. Review the official source before upgrading.
Hugging Face Transformers: v4.10.1: Patch release
Hugging Face Transformers v4.10.1. Source highlight: [Wav2Vec2] Fix normalization for non-padded tensors #13512 (@patrickvonplaten)
Hugging Face Transformers: v4.10.0: LayoutLM-v2, LayoutXLM, BEiT
Hugging Face Transformers v4.10.0. Source highlight: v4.10.0: LayoutLM-v2, LayoutXLM, BEiT
Hugging Face Transformers: v4.9.2: Patch release
Hugging Face Transformers v4.9.2. Source highlight: v4.9.2: Patch release
Hugging Face Transformers: v4.9.1: Patch release
Hugging Face Transformers v4.9.1 is published, but the available notes are too limited to assess upgrade impact. Review the official source before upgrading.
Hugging Face Transformers: v4.9.0: TensorFlow examples, CANINE, tokenizer training, ONNX rework
Hugging Face Transformers v4.9.0. Source highlight: v4.9.0: TensorFlow examples, CANINE, tokenizer training, ONNX rework
Hugging Face Transformers: Patch release: v4.8.2
Hugging Face Transformers v4.8.2. Source highlight: Patch release: v4.8.2
Hugging Face Transformers: v4.8.1: Patch release
Hugging Face Transformers v4.8.1. Source highlight: v4.8.1: Patch release
Hugging Face Transformers: v4.8.0 Integration with the Hub and Flax/JAX support
Hugging Face Transformers v4.8.0. Source highlight: v4.8.0 Integration with the Hub and Flax/JAX support
Hugging Face Transformers: v4.7.0: DETR, RoFormer, ByT5, HuBERT, support for torch 1.9.0
Hugging Face Transformers v4.7.0. Source highlight: v4.7.0: DETR, RoFormer, ByT5, Hubert, support for torch 1.9.0
Hugging Face Transformers: v4.6.1: Patch release
Hugging Face Transformers v4.6.1. Source highlight: Fix regression in models for sequence classification used for regression tasks #11785
Hugging Face Transformers: v4.6.0: ViT, DeiT, CLIP, LUKE, BigBirdPegasus, MegatronBERT
Hugging Face Transformers v4.6.0. Source highlight: v4.6.0: ViT, DeiT, CLIP, LUKE, BigBirdPegasus, MegatronBERT
Hugging Face Transformers: v4.5.1: Patch release
Hugging Face Transformers v4.5.1. Source highlight: Fix `pipeline` when used with private models (#11123)
Hugging Face Transformers: v4.5.0: BigBird, GPT Neo, Examples, Flax support
Hugging Face Transformers v4.5.0. Source highlight: v4.5.0: BigBird, GPT Neo, Examples, Flax support
Hugging Face Transformers: Patch release V4.4.2
Hugging Face Transformers v4.4.2. Source highlight: Add support for detecting intel-tensorflow version
Hugging Face Transformers: v4.4.0: S2T, M2M100, I-BERT, mBART-50, DeBERTa-v2, XLSR-Wav2Vec2
Hugging Face Transformers v4.4.0. Source highlight: v4.4.0: S2T, M2M100, I-BERT, mBART-50, DeBERTa-v2, XLSR-Wav2Vec2
Hugging Face Transformers: v4.3.3: Patch release
Hugging Face Transformers v4.3.3. Source highlight: This patch fixes an issue with the conversion for ConvBERT models: https://github.com/huggingface/transformers/pull/10314.
Hugging Face Transformers: V4.3.2: Patch release
Hugging Face Transformers v4.3.2. Source highlight: This patch release fixes the RAG model (#10094) and the detection of whether faiss is available (#10103)
Hugging Face Transformers: v4.3.1: Patch release
Hugging Face Transformers v4.3.1. Source highlight: This patch release modifies the API of the `Wav2Vec2` model: the `Wav2Vec2ForCTC` was added as a replacement of `Wav2Vec2ForMaskedLM`. `Wav2Vec2ForMaskedLM` is kept for backwards compatibility but is deprecated.
Hugging Face Transformers: v4.3.0: Wav2Vec2, ConvBERT, BORT, Amazon SageMaker
Hugging Face Transformers v4.3.0. Source highlight: Wav2Vec2 from facebook (@patrickvonplaten)
Hugging Face Transformers: v4.2.2: Patch release
Hugging Face Transformers v4.2.2. Source highlight: This patch contains two fixes:
Hugging Face Transformers: v4.2.1 Patch release
Hugging Face Transformers v4.2.1. Source highlight: This patch contains three fixes:
Hugging Face Transformers: v4.2.0: LED from AllenAI, Generation Scores, TensorFlow 2x speedup, faster import
Hugging Face Transformers v4.2.0. Source highlight: v4.2.0: LED from AllenAI, encoder-decoder templates, fast imports
Hugging Face Transformers: v4.1.1: TAPAS, MPNet, model parallelization, Sharded DDP, conda, multi-part downloads.
Hugging Face Transformers v4.1.1. Source highlight: v4.1.1: TAPAS, MPNet, model parallelization, Sharded DDP, conda, multi-part downloads.
Hugging Face Transformers: Patch release: better error message & invalid trainer attribute
Hugging Face Transformers v4.0.1. Source highlight: This patch releases introduces:
Hugging Face Transformers: Transformers v4.0.0: Fast tokenizers, model outputs, file reorganization
Hugging Face Transformers v4.0.0. Source highlight: Transformers v4.0.0-rc-1: Fast tokenizers, model outputs, file reorganization
Hugging Face Transformers v3.5.1 — Release Notes & Engineering Impact
Hugging Face Transformers v3.5.1 is published, but the available notes are too limited to assess upgrade impact. Review the official source before upgrading.
Hugging Face Transformers: v3.5.0: Model versioning, TensorFlow encoder-decoder models, new scripts, refactor of the `generate` method
Hugging Face Transformers v3.5.0. Source highlight: Model versioning, TensorFlow encoder-decoder models, new scripts, refactor of the `generate` method
Hugging Face Transformers: ProphetNet, Blenderbot, SqueezeBERT, DeBERTa
Hugging Face Transformers v3.4.0. Source highlight: ProphetNet, Blenderbot, SqueezeBERT, DeBERTa
Hugging Face Transformers v3.3.1 — Release Notes & Engineering Impact
Hugging Face Transformers v3.3.1. Source highlight: Fixes errors due to the name conflicts between the datasets library and local folder or modules named datasets.
Hugging Face Transformers v3.3.0 — Release Notes & Engineering Impact
Hugging Face Transformers v3.3.0. Source highlight: The RAG model is a retrieval-augmented generation model that can be leveraged for question-answering tasks using `RagTokenForGeneration` or `RagSequenceForGeneration` as proposed in Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks by Patrick Lewis, Ethan Perez, Aleksandara Piktus, Fa
Hugging Face Transformers: Bert Seq2Seq models, FSMT, LayoutLM, Funnel Transformer, LXMERT
Hugging Face Transformers v3.2.0. Source highlight: Bert Seq2Seq models, FSMT, Funnel Transformer, LXMERT
Hugging Face Transformers: Pegasus, DPR, self-documented outputs, new pipelines and MT support
Hugging Face Transformers v3.1.0. Source highlight: Pegasus, mBART, DPR, self-documented outputs and new pipelines
Hugging Face Transformers: Tokenizer fixes
Hugging Face Transformers v3.0.2 is published, but the available notes are too limited to assess upgrade impact. Review the official source before upgrading.
Hugging Face Transformers: Patch v3.0.1: Better backward compatibility for tokenizers
Hugging Face Transformers v3.0.1. Source highlight: Better backward-compatibility for tokenizers following v3.0.0 refactoring
Hugging Face Transformers: New tokenizer API, TensorFlow improvements, enhanced documentation & tutorials
Hugging Face Transformers v3.0.0. Source highlight: New tokenizer API, TensorFlow improvements, enhanced documentation & tutorials
Hugging Face Transformers: Longformer
Hugging Face Transformers v2.11.0. Source highlight: Longformer (@ibeltagy)
Hugging Face Transformers: Reformer, ElectraForSequenceClassification, ONNX conversion script
Hugging Face Transformers v2.10.0. Source highlight: Reformer (@patrickvonplaten)
Hugging Face Transformers: Marian
Hugging Face Transformers v2.9.1. Source highlight: A new model architecture, `MarianMTModel` with 1,008+ pretrained weights is available for machine translation in PyTorch.
Hugging Face Transformers: Trainer, TFTrainer, Multilingual BART, Encoder-decoder improvements, Generation Pipeline
Hugging Face Transformers v2.9.0. Source highlight: Trainer & TFTrainer (@julien-c)
Hugging Face Transformers: ELECTRA, Bad word filters, bugfixes & improvements
Hugging Face Transformers v2.8.0. Source highlight: ELECTRA Model (@LysandreJik)
Hugging Face Transformers: T5 Model, BART summarization example and reduced memory, translation pipeline
Hugging Face Transformers v2.7.0. Source highlight: T5 Model (@patrickvonplaten, @thomwolf )
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)
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