--- license: apache-2.0 model-index: - name: West-Ramen-7Bx4 results: - task: type: text-generation name: Text Generation dataset: name: AI2 Reasoning Challenge (25-Shot) type: ai2_arc config: ARC-Challenge split: test args: num_few_shot: 25 metrics: - type: acc_norm value: 67.58 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mayacinka/West-Ramen-7Bx4 name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: HellaSwag (10-Shot) type: hellaswag split: validation args: num_few_shot: 10 metrics: - type: acc_norm value: 85.52 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mayacinka/West-Ramen-7Bx4 name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: MMLU (5-Shot) type: cais/mmlu config: all split: test args: num_few_shot: 5 metrics: - type: acc value: 62.69 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mayacinka/West-Ramen-7Bx4 name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: TruthfulQA (0-shot) type: truthful_qa config: multiple_choice split: validation args: num_few_shot: 0 metrics: - type: mc2 value: 61.0 source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mayacinka/West-Ramen-7Bx4 name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: Winogrande (5-shot) type: winogrande config: winogrande_xl split: validation args: num_few_shot: 5 metrics: - type: acc value: 81.22 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mayacinka/West-Ramen-7Bx4 name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: GSM8k (5-shot) type: gsm8k config: main split: test args: num_few_shot: 5 metrics: - type: acc value: 58.0 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mayacinka/West-Ramen-7Bx4 name: Open LLM Leaderboard --- ## 🧩 Configuration ```yaml base_model: /home/Ubuntu/Desktop/mergekit/models/Mistral-7B-Instruct-v0.2 gate_mode: hidden dtype: bfloat16 experts: - source_model: /home/Ubuntu/Desktop/mergekit/models/Mistral-7B-Instruct-v0.2 positive_prompts: - "instructions" - "concise" - "straightforward" - "helpful" - "assistant" negative_prompts: - "vague" - "inaccurate" - "verbose" - "complicated" - "speculative" - source_model: /home/Ubuntu/Desktop/mergekit/models/NeuralOmniWestBeaglake-7B positive_prompts: - "storytelling" - "role play" - "imagine" - "artistic" - "narrative" - source_model: /home/Ubuntu/Desktop/mergekit/models/Kunoichi-DPO-v2-7B positive_prompts: - "reason" - "think step by step" - "logic" - "knowledge" negative_prompts: - "artistic" - "speculative" - "playful" - source_model: /home/Ubuntu/Desktop/mergekit/models/Starling-LM-7B-alpha positive_prompts: - "code" - "python" - "javascript" - "react" - "clear" - "programming" negative_prompts: - "error" - "art" - "role play" ``` ## 💻 Usage ```python !pip install -qU transformers bitsandbytes accelerate from transformers import AutoTokenizer import transformers import torch model = "mayacinka/West-Ramen-7Bx4" tokenizer = AutoTokenizer.from_pretrained(model) pipeline = transformers.pipeline( "text-generation", model=model, model_kwargs={"torch_dtype": torch.float16, "load_in_4bit": True}, ) messages = [{"role": "user", "content": "Explain what a Mixture of Experts is in less than 100 words."}] prompt = pipeline.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True) 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"]) ``` # [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_mayacinka__West-Ramen-7Bx4) | Metric |Value| |---------------------------------|----:| |Avg. |69.33| |AI2 Reasoning Challenge (25-Shot)|67.58| |HellaSwag (10-Shot) |85.52| |MMLU (5-Shot) |62.69| |TruthfulQA (0-shot) |61.00| |Winogrande (5-shot) |81.22| |GSM8k (5-shot) |58.00|