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Minami-su/Qwen1.5-7B-Chat_mistral
Qwen1.5-7B-Chat_mistral is a text generation model from Minami-su. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as other.
This is the Mistral version of Qwen1.5-7B-Chat model by Alibaba Cloud. The original codebase can be found at: (https://github.com/hiyouga/LLaMA-Factory/blob/main/tests/llamafyqwen.py). I have made modifications to mak…
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From the Hugging Face model README
This is the Mistral version of Qwen1.5-7B-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
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:
After:

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:
from transformers import AutoModelForCausalLM, AutoTokenizer, TextStreamer
tokenizer = AutoTokenizer.from_pretrained("Minami-su/Qwen1.5-7B-Chat_mistral")
model = AutoModelForCausalLM.from_pretrained("Minami-su/Qwen1.5-7B-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=32768, streamer=streamer)
load in 4bit
hf-causal (pretrained=Qwen1.5-7B-Chat), limit: None, provide_description: False, num_fewshot: 0, batch_size: 8
| Task |Version| Metric |Value | |Stderr|
|-------------|------:|--------|-----:|---|-----:|
|arc_challenge| 0|acc |0.4155|± |0.0144|
| | |acc_norm|0.4480|± |0.0145|
|truthfulqa_mc| 1|mc1 |0.3513|± |0.0167|
| | |mc2 |0.5165|± |0.0159|
|winogrande | 0|acc |0.6330|± |0.0135|
load in 4bit
hf-causal (pretrained=Qwen1.5-7B-Chat_mistral), limit: None, provide_description: False, num_fewshot: 0, batch_size: 16
| Task |Version| Metric |Value | |Stderr|
|-------------|------:|--------|-----:|---|-----:|
|arc_challenge| 0|acc |0.4172|± |0.0144|
| | |acc_norm|0.4480|± |0.0145|
|truthfulqa_mc| 1|mc1 |0.3488|± |0.0167|
| | |mc2 |0.5161|± |0.0159|
|winogrande | 0|acc |0.6306|± |0.0136|