64 lines
2.3 KiB
Markdown
64 lines
2.3 KiB
Markdown
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---
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license: other
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license_name: qwen
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license_link: >-
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https://github.com/QwenLM/Qwen/blob/main/Tongyi%20Qianwen%20LICENSE%20AGREEMENT
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language:
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- en
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- zh
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library_name: transformers
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pipeline_tag: text-generation
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inference: false
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tags:
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- llama
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- qwen
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- qwen1.5
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- qwen2
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---
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This is the LLaMAfied version of [Qwen1.5-7B-Chat](https://huggingface.co/Qwen/Qwen1.5-7B-Chat) model by Alibaba Cloud.
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The original codebase can be found at: (https://github.com/hiyouga/LLaMA-Factory/blob/main/tests/llamafy_qwen.py).
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I have made modifications to make it compatible with qwen1.5.
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This model is converted with https://github.com/Minami-su/character_AI_open/blob/main/llamafy_qwen_v2.py
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Usage:
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer, TextStreamer
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tokenizer = AutoTokenizer.from_pretrained("Minami-su/Qwen1.5-7B-Chat_llamafy")
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model = AutoModelForCausalLM.from_pretrained("Minami-su/Qwen1.5-7B-Chat_llamafy", torch_dtype="auto", device_map="auto")
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streamer = TextStreamer(tokenizer, skip_prompt=True, skip_special_tokens=True)
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messages = [
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{"role": "user", "content": "Who are you?"}
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]
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inputs = tokenizer.apply_chat_template(messages, tokenize=True, add_generation_prompt=True, return_tensors="pt")
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inputs = inputs.to("cuda")
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generate_ids = model.generate(inputs,max_length=2048, streamer=streamer)
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```
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## Test
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load in 4bit
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```
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hf-causal (pretrained=Qwen1.5-7B-Chat), limit: None, provide_description: False, num_fewshot: 0, batch_size: 8
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| Task |Version| Metric |Value | |Stderr|
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|-------------|------:|--------|-----:|---|-----:|
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|arc_challenge| 0|acc |0.4155|± |0.0144|
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| | |acc_norm|0.4480|± |0.0145|
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|truthfulqa_mc| 1|mc1 |0.3513|± |0.0167|
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| | |mc2 |0.5165|± |0.0159|
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|winogrande | 0|acc |0.6330|± |0.0135|
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```
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load in 4bit
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```
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hf-causal (pretrained=Qwen1.5-7B-Chat_llamafy), limit: None, provide_description: False, num_fewshot: 0, batch_size: 8
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| Task |Version| Metric |Value | |Stderr|
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|-------------|------:|--------|-----:|---|-----:|
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|arc_challenge| 0|acc |0.4172|± |0.0144|
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| | |acc_norm|0.4488|± |0.0145|
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|truthfulqa_mc| 1|mc1 |0.3501|± |0.0167|
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| | |mc2 |0.5164|± |0.0159|
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|winogrande | 0|acc |0.6306|± |0.0136|
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```
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```
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