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Thursday, 15 May 2025

Falcon-Edge: A series of powerful, universal, fine-tunable 1.58bit language models.

Hugging Face 1 year ago 11

Falcon-Edge released language models in 1.58-bit ternary format available in 1 billion and 3 billion parameter sizes for both inference and fine-tuning. The models were pre-trained on 1.5 trillion tokens and released with bfloat16 variants, pre-quantized BitNet weights, and a Python package called onebitllms to enable community fine-tuning. The release enables developers to deploy compressed models on edge devices while maintaining competitive performance on standard benchmarks.

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The Transformers Library: standardizing model definitions

Hugging Face 1 year ago 52

The Hugging Face Transformers library is positioning itself as the standard model definition layer across the machine learning ecosystem, integrating with popular training frameworks like Axolotl and inference engines like vLLM so that a model added to Transformers becomes immediately available across these tools. The library currently supports over 300 model architectures with approximately 3 new architectures added weekly, and recent integrations allow seamless interoperability such as converting models between Transformers and llama.cpp formats. The team plans to simplify model contributions by standardizing APIs and reducing redundant components, lowering the barrier for creators to release models that work across multiple downstream libraries without separate implementations.

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