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README.md
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---
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license: other
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license_name: tongyi-qianwen
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license_link: https://huggingface.co/Qwen/Qwen2-7B/blob/main/LICENSE
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language:
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- en
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pipeline_tag: text-generation
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tags:
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- chat
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- qwen
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- qwen2
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- finetune
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- chatml
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- OpenHermes-2.5
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- HelpSteer2
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- Orca
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- SlimOrca
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library_name: transformers
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inference: false
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model_creator: MaziyarPanahi
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quantized_by: MaziyarPanahi
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base_model: Qwen/Qwen2-7B
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model_name: Qwen2-7B-Instruct-v0.5
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datasets:
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- nvidia/HelpSteer2
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- teknium/OpenHermes-2.5
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- microsoft/orca-math-word-problems-200k
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- Open-Orca/SlimOrca
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---
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<img src="./qwen2-fine-tunes-maziyar-panahi.webp" alt="Qwen2 fine-tune" width="500" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
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# MaziyarPanahi/Qwen2-7B-Instruct-v0.5
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This is a fine-tuned version of the `Qwen/Qwen2-7B` model. It aims to improve the base model across all benchmarks.
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# ⚡ Quantized GGUF
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All GGUF models are available here: [MaziyarPanahi/Qwen2-7B-Instruct-v0.5](https://huggingface.co/MaziyarPanahi/Qwen2-7B-Instruct-v0.5)
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# 🏆 [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
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coming soon!
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# Prompt Template
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This model uses `ChatML` prompt template:
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```
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<|im_start|>system
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{System}
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<|im_end|>
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<|im_start|>user
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{User}
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<|im_end|>
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<|im_start|>assistant
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{Assistant}
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````
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# How to use
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```python
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# Use a pipeline as a high-level helper
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from transformers import pipeline
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messages = [
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{"role": "user", "content": "Who are you?"},
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]
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pipe = pipeline("text-generation", model="MaziyarPanahi/Qwen2-7B-Instruct-v0.5")
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pipe(messages)
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# Load model directly
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from transformers import AutoTokenizer, AutoModelForCausalLM
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tokenizer = AutoTokenizer.from_pretrained("MaziyarPanahi/Qwen2-7B-Instruct-v0.5")
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model = AutoModelForCausalLM.from_pretrained("MaziyarPanahi/Qwen2-7B-Instruct-v0.5")
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```
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