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🤗 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.
- 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
PyTorch’s torch.nn.functional.scaled_dot_product_attention...
- Pipelines
torch_dtype (str or torch.dtype, optional) — Sent directly...
- Installation
Install 🤗 Transformers for whichever deep learning library...
- Time Series Transformer
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.
🤗 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.
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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.
9 oct. 2019 · Recent progress in natural language processing has been driven by advances in both model architecture and model pretraining. Transformer architectures have facilitated building higher-capacity...
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