---
license: mit
datasets:
- liumindmind/NekoQA-10K
language:
- zh
base_model:
- hhzm/qwen3-14b-meow
pipeline_tag: text-generation
---

# **DISCLAIMER: This model is an experimental project by a beginner in fine-tuning. Output quality is not guaranteed, so please do not use it for production or professional work.**


```sh
pip install "vllm>=0.8.5"
```

Use `--enable-auto-tool-choice --tool-call-parser hermes` to enable tool calling.

```
# enable reasoning
VLLM_ALLOW_LONG_MAX_MODEL_LEN=1 vllm serve hhzm/qwen3-14b-meow-gptq-w8a8 --reasoning-parser qwen3 --enable-auto-tool-choice --tool-call-parser hermes 

# disable reasoning
VLLM_ALLOW_LONG_MAX_MODEL_LEN=1 vllm serve hhzm/qwen3-14b-meow-gptq-w8a8 --chat-template qwen3-14b-meow-gptq-w8a8/qwen3_nonthinking.jinja --enable-auto-tool-choice --tool-call-parser hermes 
```

For longer context window (>40960), use YaRN, factor is adjustable.

The environment variable VLLM_ALLOW_LONG_MAX_MODEL_LEN=1 is required to enable context lengths greater than 40960.

```sh
# enable YaRN rope scaling
--rope-scaling '{"rope_type":"yarn","factor":4.0,"original_max_position_embeddings":32768}' --max_model_len 131072 
```

Expected to be compatible with older Volta and Turing generation GPUs, as it was trained with FlashAttention-2 disabled, and using FP16.