--- language: - en license: other library_name: transformers tags: - chat - qwen - qwen2 - finetune - chatml base_model: Qwen/Qwen2-72B-Instruct license_name: tongyi-qianwen license_link: https://huggingface.co/Qwen/Qwen2-72B-Instruct/blob/main/LICENSE pipeline_tag: text-generation inference: false model_creator: MaziyarPanahi quantized_by: MaziyarPanahi model-index: - name: calme-2.1-qwen2-72b results: - task: type: text-generation name: Text Generation dataset: name: IFEval (0-Shot) type: HuggingFaceH4/ifeval args: num_few_shot: 0 metrics: - type: inst_level_strict_acc and prompt_level_strict_acc value: 81.63 name: strict accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=MaziyarPanahi/calme-2.1-qwen2-72b name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: BBH (3-Shot) type: BBH args: num_few_shot: 3 metrics: - type: acc_norm value: 57.33 name: normalized accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=MaziyarPanahi/calme-2.1-qwen2-72b name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: MATH Lvl 5 (4-Shot) type: hendrycks/competition_math args: num_few_shot: 4 metrics: - type: exact_match value: 36.03 name: exact match source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=MaziyarPanahi/calme-2.1-qwen2-72b name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: GPQA (0-shot) type: Idavidrein/gpqa args: num_few_shot: 0 metrics: - type: acc_norm value: 17.45 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=MaziyarPanahi/calme-2.1-qwen2-72b name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: MuSR (0-shot) type: TAUR-Lab/MuSR args: num_few_shot: 0 metrics: - type: acc_norm value: 20.15 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=MaziyarPanahi/calme-2.1-qwen2-72b name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: MMLU-PRO (5-shot) type: TIGER-Lab/MMLU-Pro config: main split: test args: num_few_shot: 5 metrics: - type: acc value: 49.05 name: accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=MaziyarPanahi/calme-2.1-qwen2-72b name: Open LLM Leaderboard --- Qwen2 fine-tune # MaziyarPanahi/calme-2.1-qwen2-72b This model is a fine-tuned version of the powerful `Qwen/Qwen2-72B-Instruct`, pushing the boundaries of natural language understanding and generation even further. My goal was to create a versatile and robust model that excels across a wide range of benchmarks and real-world applications. ## Use Cases This model is suitable for a wide range of applications, including but not limited to: - Advanced question-answering systems - Intelligent chatbots and virtual assistants - Content generation and summarization - Code generation and analysis - Complex problem-solving and decision support # ⚡ Quantized GGUF All GGUF models are available here: [MaziyarPanahi/calme-2.1-qwen2-72b-GGUF](https://huggingface.co/MaziyarPanahi/calme-2.1-qwen2-72b-GGUF) # 🏆 [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard) Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_MaziyarPanahi__calme-2.1-qwen2-72b) | Metric |Value| |-------------------|----:| |Avg. |43.61| |IFEval (0-Shot) |81.63| |BBH (3-Shot) |57.33| |MATH Lvl 5 (4-Shot)|36.03| |GPQA (0-shot) |17.45| |MuSR (0-shot) |20.15| |MMLU-PRO (5-shot) |49.05| | Tasks |Version|Filter|n-shot|Metric|Value | |Stderr| |--------------|------:|------|-----:|------|-----:|---|-----:| |truthfulqa_mc2| 2|none | 0|acc |0.6761|± |0.0148| | Tasks |Version|Filter|n-shot|Metric|Value | |Stderr| |----------|------:|------|-----:|------|-----:|---|-----:| |winogrande| 1|none | 5|acc |0.8248|± |0.0107| | Tasks |Version|Filter|n-shot| Metric |Value | |Stderr| |-------------|------:|------|-----:|--------|-----:|---|-----:| |arc_challenge| 1|none | 25|acc |0.6852|± |0.0136| | | |none | 25|acc_norm|0.7184|± |0.0131| |Tasks|Version| Filter |n-shot| Metric |Value | |Stderr| |-----|------:|----------------|-----:|-----------|-----:|---|-----:| |gsm8k| 3|strict-match | 5|exact_match|0.8582|± |0.0096| | | |flexible-extract| 5|exact_match|0.8893|± |0.0086| # Prompt Template This model uses `ChatML` prompt template: ``` <|im_start|>system {System} <|im_end|> <|im_start|>user {User} <|im_end|> <|im_start|>assistant {Assistant} ```` # How to use ```python # Use a pipeline as a high-level helper from transformers import pipeline messages = [ {"role": "user", "content": "Who are you?"}, ] pipe = pipeline("text-generation", model="MaziyarPanahi/calme-2.1-qwen2-72b") pipe(messages) # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("MaziyarPanahi/calme-2.1-qwen2-72b") model = AutoModelForCausalLM.from_pretrained("MaziyarPanahi/calme-2.1-qwen2-72b") ``` # Ethical Considerations As with any large language model, users should be aware of potential biases and limitations. We recommend implementing appropriate safeguards and human oversight when deploying this model in production environments. # [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard) Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_MaziyarPanahi__calme-2.1-qwen2-72b) | Metric |Value| |-------------------|----:| |Avg. |43.61| |IFEval (0-Shot) |81.63| |BBH (3-Shot) |57.33| |MATH Lvl 5 (4-Shot)|36.03| |GPQA (0-shot) |17.45| |MuSR (0-shot) |20.15| |MMLU-PRO (5-shot) |49.05|