ISTA-DASLab/gemma-3-27b-it-GPTQ-4b-128g
image-text-to-text model by ISTA-DASLab
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Model card & documentation
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This model was obtained by quantizing the weights of gemma-3-27b-it to INT4 data type. This optimization reduces the number of bits per parameter from 16 to 4, reducing the disk size and GPU memory requirements by approximately 75%. Only the weights of the linear operators within languagemodel transformers blocks are quantized. Vision model and multimodal projection are kept in original precision. Weights are quantized using a symmetric per-group scheme, with group size 128. The…
Read the full model card ↗ · Preview checked 2026-10-30T23:07:05.973Z
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Model overview
ISTA-DASLab/gemma-3-27b-it-GPTQ-4b-128g is a image-text-to-text model repository published by ISTA-DASLab on Hugging Face. The source reports the transformers library.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- image-text-to-text
- Library
- transformers
- Recent downloads (30 days)
- 666,546
- Cumulative likes
- 44
- Hugging Face trending score
- 0
- Reported safetensors parameters
- 27,632,394,708
- Architecture
- Gemma3ForConditionalGeneration
- License
- gemma
- Access
- Not gated by Hugging Face
- Created
- 2025-03-14T07:58:52.000Z
- Last modified
- 2025-03-20T14:15:41.000Z
Compatibility and lineage
Language coverage was not reported.
Reported base models: google/gemma-3-27b-it
Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.
Use and evaluate
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-10-18T06:44:02.474Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.