chris320211/smoothquant-qwen25-15b-g52xlarge-vllm
text-generation model by chris320211
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Model card & documentation
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A native vLLM checkpoint of chris320211/smoothquant-qwen25-15b-g52xlarge, the SmoothQuant quantization of Qwen/Qwen2.5-1.5B-Instruct. The int8 weights are the same bytes, renamed into the compressed-tensors format (int-quantized: per-channel int8 weights, dynamic per-token int8 activations). No custom code, no trustremotecode. Measured with vLLM 0.30.0 on NVIDIA GeForce RTX 3090, against vLLM fp16 of Qwen/Qwen2.5-1.5B-Instruct. WikiText-2 test, 2048-token windows (65504 tokens), the same windows as the HF benchmark in…
Read the full model card ↗ · Preview checked 2026-10-28T07:33:03.795Z
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Model overview
chris320211/smoothquant-qwen25-15b-g52xlarge-vllm is a text-generation model repository published by chris320211 on Hugging Face. A library was not reported.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- text-generation
- Library
- Not reported
- Recent downloads (30 days)
- 0
- Cumulative likes
- 0
- Hugging Face trending score
- 0
- Reported safetensors parameters
- 1,543,714,304
- Architecture
- Qwen2ForCausalLM
- License
- apache-2.0
- Access
- Not gated by Hugging Face
- Created
- 2026-10-28T06:37:36.000Z
- Last modified
- 2026-10-28T06:37:59.000Z
Compatibility and lineage
Language coverage was not reported.
Reported base models: Qwen/Qwen2.5-1.5B-Instruct
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 2026-10-28T06:47:50.589Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.