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🤗 Transformers State-of-the-art Machine Learning for PyTorch , TensorFlow , and JAX . Using pretrained models can reduce your compute costs, carbon footprint, and save you the time and resources required to train a model from scratch.
- Time Series Transformer
A transformers.modeling_outputs.Seq2SeqTSModelOutput or a...
- Bert
Overview. The BERT model was proposed in BERT: Pre-training...
- Tokenizer
Parameters . new_tokens (str, tokenizers.AddedToken or a...
- Train With a Script
The example script downloads and preprocesses a dataset from...
- Trainer
Trainer is a simple but feature-complete training and eval...
- Training on One GPU
For an example of using torch.compile with 🤗 Transformers,...
- Pipelines
Pipelines. The pipelines are a great and easy way to use...
- Installation
Install 🤗 Transformers for whichever deep learning library...
- Time Series Transformer
GPT-2 is a large transformer-based language model with 1.5 billion parameters, trained on a dataset[1] of 8 million web pages. GPT-2 is trained with a simple objective: predict the next word, given all of the previous words within some text.
Train state-of-the-art models in 3 lines of code. Deep interoperability between TensorFlow 2.0 and PyTorch models. Move a single model between TF2.0/PyTorch frameworks at will. Seamlessly pick the right framework for training, evaluation, production.
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. These models can be applied on: 📝 Text, for tasks like text classification, information extraction, question answering, summarization ...
TLDR; Phi-3 introduces new ROPE scaling methods, which seems to scale fairly well! A 3b and a Phi-3-mini is available in two context-length variants—4K and 128K tokens. It is the first model in its class to support a context window of up to 128K tokens, with little impact on quality. Phi-3 by @gugarosa in #30423; JetMoE
20 nov. 2023 · Hugging Face Transformers offers cutting-edge machine learning tools for PyTorch, TensorFlow, and JAX. This platform provides easy-to-use APIs and tools for downloading and training top-tier pretrained models.
🤗 transformers is a library maintained by Hugging Face and the community, for state-of-the-art Machine Learning for Pytorch, TensorFlow and JAX. It provides thousands of pretrained models to perform tasks on different modalities such as text, vision, and audio. We are a bit biased, but we really like 🤗 transformers!
