
* Initial add model additions * Test * All weights loading * Can perform full forward pass * Local and remote the same * Matching local and remote * Fixup * Idefics2Model importable; fixup docstrings * Don't skip by default * Remove deprecated use_resampler arg * Remove self.config * DecoupledLinear takes config * Tidy up * Enable eager attention and tidy up * Most tests passing * Update for batch of processed images * Add image processor * Update doc pages * Update conversion script * Remove erroneous breakpoint * Remove accidendtal spelling change * Update to reflect changes on hub - make generate work * Fix up * Image processor tests * Update tests * Add a processor * Add a processor * Update convert script * Update modeling file - remove fixmes * Bug fix * Add processing test * Use processor * Fix up * Update src/transformers/models/idefics2/modeling_idefics2.py Co-authored-by: Victor SANH <victorsanh@gmail.com> * Update src/transformers/models/idefics2/modeling_idefics2.py Co-authored-by: Victor SANH <victorsanh@gmail.com> * Fix test * Update config - PR comments and defaults align with checkpoint * Reviewer comments * Add copied froms for flahs attention * Update src/transformers/models/idefics2/modeling_idefics2.py Co-authored-by: Victor SANH <victorsanh@gmail.com> * Apply suggestions from code review Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * Remove qk_layer_norm and freeze_layers functionality * Fix * Remove freeze_layer options from config * Sync with upstream main * Fix attention shapes siglip * Remove Llava-next refs - TO REBASE * Use AutoModel for text model * Add comment to explain vision embeddings * Fix issue with tie_word_embeddings * Address review comments * Fix and fix up * Chat templates for idefics * Fix copies * Fix * Add layer norms to FA2 * Fix tests * Apply suggestions from code review Co-authored-by: Victor SANH <victorsanh@gmail.com> * Fix * Review comments * Update src/transformers/models/idefics2/modeling_idefics2.py Co-authored-by: Victor SANH <victorsanh@gmail.com> * Update inputs merger * Merge weights in correct order * Update convert script * Update src/transformers/models/idefics2/processing_idefics2.py Co-authored-by: Victor SANH <victorsanh@gmail.com> * Update template * Model code examples (fix idefics too) * More review comments * Tidy up * Update processing * Fix attention mask preparation * Update inputs_merger inputs * Vectorize inputs_merger * Update src/transformers/models/idefics2/__init__.py Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * Update src/transformers/models/idefics2/modeling_idefics2.py * Review comments * saying bye to the `qk_layer_norms` * Simplify * Update latents * Remove erroneuous readme changes * Return images when applying chat template * Fix bug - prompt images are for a single sample * Update src/transformers/models/idefics2/modeling_idefics2.py * image splitting * fix test * some more comment * some comment * Apply suggestions from code review Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/idefics2/image_processing_idefics2.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update processor * Update model tests * Update src/transformers/models/idefics2/processing_idefics2.py Co-authored-by: Victor SANH <victorsanh@gmail.com> * Update src/transformers/models/idefics2/processing_idefics2.py Co-authored-by: Victor SANH <victorsanh@gmail.com> * Don't add BOS in template * Update src/transformers/models/idefics2/processing_idefics2.py Co-authored-by: Victor SANH <victorsanh@gmail.com> * Remove index in examples * Update tests to reflect #13 * Update src/transformers/models/idefics2/processing_idefics2.py Co-authored-by: Victor SANH <victorsanh@gmail.com> * PR comment - consistent typing * Update readme and model doc * Update docs * Update checkpoint references * Update examples * Fix and update tests * Small addition * Update tests - remove copied from as no ignore placement copy could be found * Update example * small fixes * Update docs/source/en/model_doc/idefics2.md Co-authored-by: Victor SANH <victorsanh@gmail.com> * Update docs/source/en/model_doc/idefics2.md Co-authored-by: Victor SANH <victorsanh@gmail.com> * Update README.md Co-authored-by: Victor SANH <victorsanh@gmail.com> * Connector model as bridge * Fix up * Fix up * Don't pass model inputs for generation kwargs update * IDEFICS-2 -> Idefics2 * Remove config archive name * IDEFICS-2 -> Idefics2 * Add back llava-next * Update readmes * Add requirements for processor tester * Use custom convert_to_rgb to avoid possible BC * Fix doc example * Fix doc example * Skip model doc tests - as model to large * More doc example - account for image splitting * Update src/transformers/image_transforms.py * Fix config doctest --------- Co-authored-by: Pablo Montalvo <39954772+molbap@users.noreply.github.com> Co-authored-by: ArthurZucker <arthur.zucker@gmail.com> Co-authored-by: Victor SANH <victorsanh@gmail.com> Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
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🤗 Transformers
State-of-the-art Machine Learning for PyTorch, TensorFlow, and JAX.
🤗 Transformers provides APIs and tools to easily download and train state-of-the-art pretrained models. Using pretrained models can reduce your compute costs, carbon footprint, and save you the time and resources required to train a model from scratch. These models support common tasks in different modalities, such as:
📝 Natural Language Processing: text classification, named entity recognition, question answering, language modeling, summarization, translation, multiple choice, and text generation.
🖼️ Computer Vision: image classification, object detection, and segmentation.
🗣️ Audio: automatic speech recognition and audio classification.
🐙 Multimodal: table question answering, optical character recognition, information extraction from scanned documents, video classification, and visual question answering.
🤗 Transformers support framework interoperability between PyTorch, TensorFlow, and JAX. This provides the flexibility to use a different framework at each stage of a model's life; train a model in three lines of code in one framework, and load it for inference in another. Models can also be exported to a format like ONNX and TorchScript for deployment in production environments.
Join the growing community on the Hub, forum, or Discord today!
If you are looking for custom support from the Hugging Face team

Contents
The documentation is organized into five sections:
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GET STARTED provides a quick tour of the library and installation instructions to get up and running.
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TUTORIALS are a great place to start if you're a beginner. This section will help you gain the basic skills you need to start using the library.
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HOW-TO GUIDES show you how to achieve a specific goal, like finetuning a pretrained model for language modeling or how to write and share a custom model.
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CONCEPTUAL GUIDES offers more discussion and explanation of the underlying concepts and ideas behind models, tasks, and the design philosophy of 🤗 Transformers.
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API describes all classes and functions:
- MAIN CLASSES details the most important classes like configuration, model, tokenizer, and pipeline.
- MODELS details the classes and functions related to each model implemented in the library.
- INTERNAL HELPERS details utility classes and functions used internally.
Supported models and frameworks
The table below represents the current support in the library for each of those models, whether they have a Python tokenizer (called "slow"). A "fast" tokenizer backed by the 🤗 Tokenizers library, whether they have support in Jax (via Flax), PyTorch, and/or TensorFlow.