Disclaimer:

The model is reproduced based on the paper VPTQ: Extreme Low-bit Vector Post-Training Quantization for Large Language Models github and arXiv

The model itself is sourced from a community release.

It is intended only for experimental purposes.

Users are responsible for any consequences arising from the use of this model.

Note:

The PPL test results are for reference only and were collected using GPTQ testing script.

{
    "ctx_2048": {
        "wikitext2": 16.465784072875977,
        "c4": 23.362998962402344,
        "c4-new": 28.253490447998047
    },
    "ctx_4096": {
        "wikitext2": 14.906161308288574,
        "c4": 22.091983795166016,
        "c4-new": 26.17787742614746
    },
    "ctx_8192": {
        "wikitext2": 14.027444839477539,
        "c4": 15.35131549835205,
        "c4-new": 25.94689178466797
    }
}
Downloads last month

-

Downloads are not tracked for this model. How to track
Inference Providers NEW
This model is not currently available via any of the supported Inference Providers.
The model cannot be deployed to the HF Inference API: The model has no library tag.

Model tree for VPTQ-community/Mistral-Large-Instruct-2407-v16-k65536-256-woft

Quantized
(22)
this model

Collection including VPTQ-community/Mistral-Large-Instruct-2407-v16-k65536-256-woft