◐ModelLanguage & NLPFree
Transformers
Hugging Face Transformers: state-of-the-art pre-trained models for NLP, vision, audio, and multimodal tasks.
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평점★ 4.9
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Transformers
The Hugging Face transformers library is the de-facto standard for accessing and running thousands of pre-trained models. It provides a unified API across PyTorch, TensorFlow, and JAX for text, image, audio, and multimodal inference and fine-tuning.
Key Features
- Hub integration — one-line download of 500,000+ models from huggingface.co
- Pipelines API — zero-boilerplate inference for text generation, classification, NER, translation, summarization, and more
- Trainer API — full fine-tuning loop with mixed precision, gradient accumulation, and distributed training
- Generation utilities — beam search, sampling, contrastive search, speculative decoding
- Quantization — bitsandbytes 4-bit/8-bit, GPTQ, and AWQ support built-in
- TGI / vLLM compatible — models load into all major serving runtimes
Quick Start
pip install transformers torch
from transformers import pipeline
generator = pipeline("text-generation", model="meta-llama/Llama-3.2-1B-Instruct")
result = generator("The future of AI agents is", max_new_tokens=50)
print(result[0]["generated_text"])
Install via ai-supply
npx ai-supply add huggingface-transformers
Curated mirror of the open-source Transformers project (Apache-2.0). Install upstream from the repository.