初始化项目，由ModelHub XC社区提供模型

Model: drawais/Qwen3-32B-AWQ-INT4
Source: Original Platform

README.md

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+---
+license: apache-2.0
+base_model: Qwen/Qwen3-32B
+tags:
+  - quantized
+  - 4-bit
+  - int4
+  - qwen3
+language:
+  - en
+pipeline_tag: text-generation
+---
+
+# Qwen3-32B-AWQ-INT4
+
+INT4 quantization of [`Qwen/Qwen3-32B`](https://huggingface.co/Qwen/Qwen3-32B). Built to run on a single 24 GB+ GPU.
+
+## Footprint
+
+| | |
+|---|---|
+| Source params | 32B |
+| Quantized weights | ~18 GB on disk |
+| Inference VRAM (incl. KV cache @ 32K context) | ~24 GB |
+
+Fits any 24 GB+ GPU: RTX 3090 / 4090 / 5090, A5000, A6000, A100 40GB, etc.
+
+## Bench
+
+Scored on [`drawais/needle-1M-bench-mvp`](https://huggingface.co/datasets/drawais/needle-1M-bench-mvp) (50K-token haystack, real arxiv text):
+
+| Metric | Score |
+|---|---|
+| Overall recall | **100.0%** |
+| Paper-anchored | 100.0% |
+| Synthetic codes | 100.0% |
+
+## Quick start
+
+```bash
+vllm serve drawais/Qwen3-32B-AWQ-INT4 --quantization awq_marlin --max-model-len 32768
+```
+
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+tok = AutoTokenizer.from_pretrained("drawais/Qwen3-32B-AWQ-INT4")
+model = AutoModelForCausalLM.from_pretrained("drawais/Qwen3-32B-AWQ-INT4", device_map="auto")
+```
+
+## Context length
+
+Native: 40,960 tokens (inherits from base model). For longer contexts, enable YaRN rope-scaling per the base model's config.
+
+## License
+
+Apache 2.0 (inherits from base model).