Pre-trained models (SqueezeLLM)
Collection
15 items
•
Updated
Model Card
- Base model:
meta-llama/Meta-Llama-3-70B - Quantization method: SqueezeLLM
- Target bit-width: 2
- Backend kernel: Any-Precision-LLM kernel (
ap-gemv) - Calibration data: RedPajama (1024 sentences / 4096 tokens)
- Calibration objective: Next-token prediction
How to run
- Follow the instruction in https://github.com/snu-mllab/GuidedQuant.
References
- Downloads last month
- 13
Inference Providers
NEW
This model isn't deployed by any Inference Provider.
🙋
Ask for provider support
Model tree for jusjinuk/Meta-Llama-3-70B-2bit-SqueezeLLM
Base model
meta-llama/Meta-Llama-3-70B