--- license: apache-2.0 tags: - merge - mergekit - lazymergekit - prometheus-eval/prometheus-8x7b-v2.0 - mistralai/Mixtral-8x7B-Instruct-v0.1 base_model: - prometheus-eval/prometheus-8x7b-v2.0 - mistralai/Mixtral-8x7B-Instruct-v0.1 model-index: - name: Merge-Mixtral-Prometheus-8x7B 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: 57.44 name: strict accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=vicgalle/Merge-Mixtral-Prometheus-8x7B 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: 34.65 name: normalized accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=vicgalle/Merge-Mixtral-Prometheus-8x7B 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: 8.31 name: exact match source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=vicgalle/Merge-Mixtral-Prometheus-8x7B 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: 7.83 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=vicgalle/Merge-Mixtral-Prometheus-8x7B 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: 9.59 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=vicgalle/Merge-Mixtral-Prometheus-8x7B 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: 29.82 name: accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=vicgalle/Merge-Mixtral-Prometheus-8x7B name: Open LLM Leaderboard --- # Merge-Mixtral-Prometheus-8x7B Merge-Mixtral-Prometheus-8x7B is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing): * [prometheus-eval/prometheus-8x7b-v2.0](https://huggingface.co/prometheus-eval/prometheus-8x7b-v2.0) * [mistralai/Mixtral-8x7B-Instruct-v0.1](https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1) ## 🧩 Configuration ```yaml models: - model: prometheus-eval/prometheus-8x7b-v2.0 parameters: weight: 1.0 - model: mistralai/Mixtral-8x7B-Instruct-v0.1 parameters: weight: 1.0 merge_method: linear dtype: bfloat16 ``` ## 💻 Usage ```python !pip install -qU transformers accelerate from transformers import AutoTokenizer import transformers import torch model = "vicgalle/test-merge-3" messages = [{"role": "user", "content": "What is a large language model?"}] tokenizer = AutoTokenizer.from_pretrained(model) prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True) pipeline = transformers.pipeline( "text-generation", model=model, torch_dtype=torch.float16, device_map="auto", ) outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95) print(outputs[0]["generated_text"]) ``` ## Paper citation Paper: https://arxiv.org/abs/2406.07188 # [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_vicgalle__Merge-Mixtral-Prometheus-8x7B) | Metric |Value| |-------------------|----:| |Avg. |24.61| |IFEval (0-Shot) |57.44| |BBH (3-Shot) |34.65| |MATH Lvl 5 (4-Shot)| 8.31| |GPQA (0-shot) | 7.83| |MuSR (0-shot) | 9.59| |MMLU-PRO (5-shot) |29.82|