Github Iefps Huggingface Transformers Transformers State Of The

Leo Migdal

-Nov 18, 2025, 4:10 AM

github iefps huggingface transformers transformers state of the

English | 简体中文 | 繁體中文 | 한국어 | Español | 日本語 | हिन्दी | Русский | Рortuguês | తెలుగు | Français | Deutsch | Tiếng Việt | State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow 🤗 Transformers provides thousands of pretrained models to perform tasks on different modalities such as text, vision, and audio. Transformer models can also perform tasks on several modalities combined, such as table question answering, optical character recognition, information extraction from scanned documents, video classification, and visual question answering. 🤗 Transformers provides APIs to quickly download and use those pretrained models on a given text, fine-tune them on your own datasets and then share them with the community on our model hub. At the same time, each python module defining an architecture is fully standalone and can be modified to enable quick research experiments.

English | 简体中文 | 繁體中文 | 한국어 | Español | 日本語 | हिन्दी | Русский | Português | తెలుగు | Français | Deutsch | Italiano | Tiếng Việt | العربية | اردو | বাংলা... State-of-the-art pretrained models for inference and training Transformers acts as the model-definition framework for state-of-the-art machine learning with text, computer vision, audio, video, and multimodal models, for both inference and training. It centralizes the model definition so that this definition is agreed upon across the ecosystem. transformers is the pivot across frameworks: if a model definition is supported, it will be compatible with the majority of training frameworks (Axolotl, Unsloth, DeepSpeed, FSDP, PyTorch-Lightning, ...), inference engines (vLLM, SGLang, TGI, ...),... We pledge to help support new state-of-the-art models and democratize their usage by having their model definition be simple, customizable, and efficient.

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State-of-the-art Natural Language Processing for Jax, PyTorch and TensorFlow 🤗 Transformers provides thousands of pretrained models to perform tasks on texts such as classification, information extraction, question answering, summarization, translation, text generation and more in over 100 languages. Its aim is to make cutting-edge NLP easier to use for everyone. 🤗 Transformers provides APIs to quickly download and use those pretrained models on a given text, fine-tune them on your own datasets and then share them with the community on our model hub. At the same time, each python module defining an architecture is fully standalone and can be modified to enable quick research experiments. 🤗 Transformers is backed by the three most popular deep learning libraries — Jax, PyTorch and TensorFlow — with a seamless integration between them.

It's straightforward to train your models with one before loading them for inference with the other. You can test most of our models directly on their pages from the model hub. We also offer private model hosting, versioning, & an inference API for public and private models. and get access to the augmented documentation experience Transformers is a library of pretrained natural language processing, computer vision, audio, and multimodal models for inference and training. Use Transformers to train models on your data, build inference applications, and generate text with large language models.

Explore the Hugging Face Hub today to find a model and use Transformers to help you get started right away. Transformers provides everything you need for inference or training with state-of-the-art pretrained models. Some of the main features include: Read our Philosophy to learn more about Transformers’ design principles. There was an error while loading. Please reload this page.

There was an error while loading. Please reload this page. The LLaMA model was proposed in LLaMA: Open and Efficient Foundation Language Models. It is a collection of foundation language models ranging from 7B to 65B parameters. You can request access to the weights here then use the conversion script to generate a checkpoint compatible with Hugging Face Pix2Struct is a pretrained image-to-text model for purely visual language understanding, which can be finetuned on tasks containing visually-situated language.

Pix2Struct has been fine-tuned on various tasks and datasets, ranging from image captioning and visual question answering (VQA) over different inputs (books, charts, science diagrams) to captioning UI components, and others. MEGA proposes a new approach to self-attention with each encoder layer having a multi-headed exponential moving average in addition to a single head of standard dot-product attention, giving the attention mechanism stronger positional biases. This allows MEGA to perform competitively to Transformers on standard benchmarks including LRA while also having significantly fewer parameters. MEGA’s compute efficiency allows it to scale to very long sequences, making it an attractive option for long-document NLP tasks. 🤗 Transformers provides thousands of pretrained models to perform tasks on different modalities such as text, vision, and audio. Transformer models can also perform tasks on several modalities combined, such as table question answering, optical character recognition, information extraction from scanned documents, video classification, and visual question answering.

🤗 Transformers provides APIs to quickly download and use those pretrained models on a given text, fine-tune them on your own datasets and then share them with the community on our model hub. At the same time, each python module defining an architecture is fully standalone and can be modified to enable quick research experiments. 🤗 Transformers is backed by the three most popular deep learning libraries — Jax, PyTorch and TensorFlow — with a seamless integration between them. It's straightforward to train your models with one before loading them for inference with the other. You can test most of our models directly on their pages from the model hub. We also offer private model hosting, versioning, & an inference API for public and private models.

Github Iefps Huggingface Transformers Transformers State Of The

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State-of-the-art Natural Language Processing For Jax, PyTorch And TensorFlow 🤗