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Model: Minami-su/Qwen1.5-0.5B-Chat_mistral Source: Original Platform
2026-06-01 01:21:38 +08:00
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+---
+license: other
+license_name: qwen
+license_link: >-
+  https://github.com/QwenLM/Qwen/blob/main/Tongyi%20Qianwen%20LICENSE%20AGREEMENT
+language:
+- en
+- zh
+library_name: transformers
+pipeline_tag: text-generation
+inference: false
+tags:
+- mistral
+- qwen
+- qwen1.5
+- qwen2
+---
+This is the Mistral version of [Qwen1.5-0.5B-Chat](https://huggingface.co/Qwen/Qwen1.5-0.5B-Chat) model by Alibaba Cloud.
+The original codebase can be found at: (https://github.com/hiyouga/LLaMA-Factory/blob/main/tests/llamafy_qwen.py).
+I have made modifications to make it compatible with qwen1.5.
+This model is converted with https://github.com/Minami-su/character_AI_open/blob/main/mistral_qwen2.py
+
+## special
+
+1.Before using this model, you need to modify modeling_mistral.py in transformers library
+
+2.vim /root/anaconda3/envs/train/lib/python3.9/site-packages/transformers/models/mistral/modeling_mistral.py
+
+3.find MistralAttention,
+
+4.modify q,k,v,o bias=False ----->, bias=config.attention_bias
+
+Before:
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/62d7f90b102d144db4b4245b/AKj_fwEoLUKWZ4mViYW-q.png)
+After:
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/62d7f90b102d144db4b4245b/A2gSwq9l6Zx8X1qegtgvE.png)
+
+
+## Differences between qwen2 mistral and qwen2 llamafy
+
+Compared to qwen2 llamafy,qwen2 mistral can use sliding window attention,qwen2 mistral is faster than qwen2 llamafy, and the context length is better
+
+
+Usage:
+
+```python
+
+from transformers import AutoModelForCausalLM, AutoTokenizer, TextStreamer
+tokenizer = AutoTokenizer.from_pretrained("Minami-su/Qwen1.5-0.5B-Chat_mistral")
+model = AutoModelForCausalLM.from_pretrained("Minami-su/Qwen1.5-0.5B-Chat_mistral", torch_dtype="auto", device_map="auto")
+streamer = TextStreamer(tokenizer, skip_prompt=True, skip_special_tokens=True)
+
+messages = [
+    {"role": "user", "content": "Who are you?"}
+]
+inputs = tokenizer.apply_chat_template(messages, tokenize=True, add_generation_prompt=True, return_tensors="pt")
+inputs = inputs.to("cuda")
+generate_ids = model.generate(inputs,max_length=2048, streamer=streamer)
+
+```
+
+## Test
+load in 4bit
+```
+hf-causal (pretrained=Qwen1.5-0.5B-Chat), limit: None, provide_description: False, num_fewshot: 0, batch_size: 32
+|    Task     |Version| Metric |Value |   |Stderr|
+|-------------|------:|--------|-----:|---|-----:|
+|arc_challenge|      0|acc     |0.2389|±  |0.0125|
+|             |       |acc_norm|0.2688|±  |0.0130|
+|truthfulqa_mc|      1|mc1     |0.2534|±  |0.0152|
+|             |       |mc2     |0.4322|±  |0.0151|
+|winogrande   |      0|acc     |0.5564|±  |0.0140|
+```
+load in 4bit
+```
+hf-causal (pretrained=Qwen1.5-0.5B-Chat_mistral), limit: None, provide_description: False, num_fewshot: 0, batch_size: 32
+|    Task     |Version| Metric |Value |   |Stderr|
+|-------------|------:|--------|-----:|---|-----:|
+|arc_challenge|      0|acc     |0.2398|±  |0.0125|
+|             |       |acc_norm|0.2705|±  |0.0130|
+|truthfulqa_mc|      1|mc1     |0.2534|±  |0.0152|
+|             |       |mc2     |0.4322|±  |0.0151|
+|winogrande   |      0|acc     |0.5549|±  |0.0140|
+```
+```