Downloads · 30 days
0
groxaxo/Carnice-V2-27b-AutoRound-W4A16-g128
Carnice-V2-27b-AutoRound-W4A16-g128 is a machine learning model from groxaxo. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
Carnice-V2-27b-AutoRound-W4A16-g128 is a weight-quantized checkpoint intended for efficient GPU inference, published by groxaxo. It is intended for open-source evaluation, reproducible experimentation, and compatible…
Downloads · 30 days
0
Access
Public
Updated Aug 22, 2026
Repo size
—
Likes
0
Public
Click a slice to open those files.
.md2.1 KB · 58%
From the Hugging Face model README
Carnice-V2-27b-AutoRound-W4A16-g128 is a weight-quantized checkpoint intended for efficient GPU inference, published by groxaxo.
It is intended for open-source evaluation, reproducible experimentation, and compatible local or
hosted inference workflows. The wording below is deliberately limited to what can be verified
from this repository's metadata and artifacts.
| Field | Details |
|---|---|
| Format | AWQ / AutoRound |
| Source / base | the source checkpoint identified in the repository metadata |
| Intended task | the task described by the included configuration and documentation |
| License | the license declared in the repository files |
vllm serve groxaxo/Carnice-V2-27b-AutoRound-W4A16-g128 \
--quantization awq_marlin \
--dtype float16 \
--trust-remote-code
The exact kernel and flags depend on the quantizer and architecture. Check the files and source model card before selecting a production serving configuration.
Quantization or conversion changes numerical behavior, memory use, and throughput relative to the source checkpoint; validate quality on your own workload.
Generated outputs may be inaccurate or unsuitable for a given use case. Users are responsible for testing behavior, applying appropriate safeguards, and complying with applicable licenses and laws.
<!-- polished-overview:end -->