README.md

metadata

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:

• prometheus-eval/prometheus-8x7b-v2.0
• mistralai/Mixtral-8x7B-Instruct-v0.1

🧩 Configuration

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

!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

Detailed results can be found here

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