प्रोजेक्ट के स्क्रीनशॉट
अवलोकन
Transformers serves as a centralized model-definition framework that ensures compatibility across the broader machine learning ecosystem. By standardizing model definitions, it allows seamless integration with various training frameworks like Axolotl, Unsloth, DeepSpeed, and PyTorch-Lightning, as well as inference engines such as vLLM, SGLang, and TGI. The library provides a unified API with minimal abstractions, making it accessible for researchers and developers to leverage over 1 million pretrained model checkpoints available on the Hugging Face Hub.
प्रमुख विशेषताएँ
- Unified API for pretrained models across text, vision, audio, and multimodal tasks
- Compatibility with major training frameworks and inference engines
- Access to over 1 million model checkpoints on the Hugging Face Hub
- High-level Pipeline API for easy inference across modalities
- Support for model customization and exposure of model internals
आवश्यकताएँ, इंस्टॉलेशन और त्वरित शुरुआत
उपयोग
मॉडल संगतता और उपयोग के मामले
Supports a wide range of models including Qwen, Llama, Whisper, DINOv2, BLIP, Mixtral, BART, T5, Gemma, and many others across various modalities.
लाइसेंस और जोखिम संबंधी टिप्पणियाँ
Licensed under the Apache License, Version 2.0.
Editorial verification 2026-08-09: repository URL, owner, description, license and repository statistics were reviewed. License metadata: Apache-2.0. README was fetched for the channel draft; re-check repository dependencies, releases and model terms before production use.
रिलीज़ और रखरखाव
Not stated in the repository metadata.