README.md

---
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|