Fine-tuning LLMs to 1.58bit: extreme quantization made easy

Hugging Face fine-tuned Llama3 8B models to 1.58-bit quantization using the BitNet architecture, released the models under the HF1BitLLM organization, and introduced a new quantization method called 'bitnet' in Transformers.

From the source
We have successfully fine-tuned a Llama3 8B model using the BitNet architecture, achieving strong performance on downstream tasks. The 8B models we developed are released under the HF1BitLLM organization.
huggingface.co

Visit source ↗huggingface.co

Announced: 18 Sep 2024 00:00 UTC
Detected: 03 Aug 2026 21:12 UTC (+684d after)

Other stories

Hugging Face · 28 AugThe Open ASR Leaderboard Adds Its First Global South LanguageCapability change

Amazon · 31 AugConnect an AgentCore Runtime hosted MCP server to Amazon QuickCapability change

Amazon · 31 AugAWS recognized as a Leader in The Forrester Wave: AI Infrastructure Solutions, Q4 2025Company news

Amazon · 31 Aug

Manage agents, tools and skills at scale with AWS Agent Registry

Amazon · 31 AugBuild observable enterprise agentic retrieval using Managed Amazon Bedrock Knowledge Base with AWS CloudFormationInfrastructure

Amazon · 31 AugBuild multi-tenant agentic chat applications on enterprise data with Amazon Bedrock Managed Knowledge Base