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Model: MaziyarPanahi/calme-2.2-qwen2-7b Source: Original Platform
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README.md
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README.md
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---
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language:
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- en
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license: apache-2.0
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library_name: transformers
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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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base_model: Qwen/Qwen2-7B
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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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model_name: calme-2.2-qwen2-7b
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pipeline_tag: text-generation
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inference: false
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model_creator: MaziyarPanahi
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quantized_by: MaziyarPanahi
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model-index:
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- name: calme-2.2-qwen2-7b
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results:
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: IFEval (0-Shot)
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type: HuggingFaceH4/ifeval
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args:
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num_few_shot: 0
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metrics:
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- type: inst_level_strict_acc and prompt_level_strict_acc
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value: 35.97
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name: strict accuracy
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source:
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=MaziyarPanahi/calme-2.2-qwen2-7b
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: BBH (3-Shot)
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type: BBH
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args:
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num_few_shot: 3
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metrics:
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- type: acc_norm
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value: 33.11
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name: normalized accuracy
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source:
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=MaziyarPanahi/calme-2.2-qwen2-7b
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: MATH Lvl 5 (4-Shot)
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type: hendrycks/competition_math
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args:
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num_few_shot: 4
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metrics:
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- type: exact_match
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value: 19.34
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name: exact match
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source:
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=MaziyarPanahi/calme-2.2-qwen2-7b
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: GPQA (0-shot)
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type: Idavidrein/gpqa
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args:
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num_few_shot: 0
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metrics:
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- type: acc_norm
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value: 5.48
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name: acc_norm
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source:
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=MaziyarPanahi/calme-2.2-qwen2-7b
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: MuSR (0-shot)
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type: TAUR-Lab/MuSR
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args:
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num_few_shot: 0
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metrics:
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- type: acc_norm
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value: 13.28
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name: acc_norm
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source:
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=MaziyarPanahi/calme-2.2-qwen2-7b
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: MMLU-PRO (5-shot)
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type: TIGER-Lab/MMLU-Pro
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config: main
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split: test
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args:
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num_few_shot: 5
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metrics:
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- type: acc
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value: 32.21
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name: accuracy
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source:
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=MaziyarPanahi/calme-2.2-qwen2-7b
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name: Open LLM Leaderboard
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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/calme-2.2-qwen2-7b
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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/calme-2.2-qwen2-7b-GGUF](https://huggingface.co/MaziyarPanahi/calme-2.2-qwen2-7b-GGUF)
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# 🏆 [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard)
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Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_MaziyarPanahi__calme-2.2-qwen2-7b)
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| Metric |Value|
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|-------------------|----:|
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|Avg. |23.23|
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|IFEval (0-Shot) |35.97|
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|BBH (3-Shot) |33.11|
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|MATH Lvl 5 (4-Shot)|19.34|
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|GPQA (0-shot) | 5.48|
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|MuSR (0-shot) |13.28|
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|MMLU-PRO (5-shot) |32.21|
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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/calme-2.2-qwen2-7b")
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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/calme-2.2-qwen2-7b")
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model = AutoModelForCausalLM.from_pretrained("MaziyarPanahi/calme-2.2-qwen2-7b")
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```
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