--- language: - en license: other library_name: transformers tags: - chat - qwen - qwen2 - finetune - chatml base_model: Qwen/Qwen2-72B-Instruct model_name: MaziyarPanahi/Qwen2-72B-Instruct-v0.1 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: Qwen2-72B-Instruct-v0.1 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/Qwen2-72B-Instruct-v0.1 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/Qwen2-72B-Instruct-v0.1 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/Qwen2-72B-Instruct-v0.1 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/Qwen2-72B-Instruct-v0.1 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/Qwen2-72B-Instruct-v0.1 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/Qwen2-72B-Instruct-v0.1 name: Open LLM Leaderboard --- Qwen2 fine-tune # MaziyarPanahi/Qwen2-72B-Instruct-v0.1 This is a fine-tuned version of the `Qwen/Qwen2-72B-Instruct` model. It aims to improve the base model across all benchmarks. # ⚡ Quantized GGUF All GGUF models are available here: [MaziyarPanahi/Qwen2-72B-Instruct-v0.1-GGUF](https://huggingface.co/MaziyarPanahi/Qwen2-72B-Instruct-v0.1-GGUF) # 🏆 [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard) coming soon! | 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/Qwen2-72B-Instruct-v0.1") pipe(messages) # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("MaziyarPanahi/Qwen2-72B-Instruct-v0.1") model = AutoModelForCausalLM.from_pretrained("MaziyarPanahi/Qwen2-72B-Instruct-v0.1") ``` # [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__Qwen2-72B-Instruct-v0.1) | 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|