metadata

license: apache-2.0
tags:
  - moe
  - mergekit
  - merge
  - chinese
  - arabic
  - english
  - multilingual
  - german
  - french
  - gagan3012/MetaModel
  - jeonsworld/CarbonVillain-en-10.7B-v2
  - jeonsworld/CarbonVillain-en-10.7B-v4
  - TomGrc/FusionNet_linear
  - DopeorNope/SOLARC-M-10.7B
  - VAGOsolutions/SauerkrautLM-SOLAR-Instruct
  - upstage/SOLAR-10.7B-Instruct-v1.0
  - fblgit/UNA-SOLAR-10.7B-Instruct-v1.0
model-index:
  - name: MetaModel_moex8
    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: 71.16
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Xenon1/MetaModel_moex8
          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: 88.38
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Xenon1/MetaModel_moex8
          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: 66.29
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Xenon1/MetaModel_moex8
          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: 71.91
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Xenon1/MetaModel_moex8
          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: 83.27
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Xenon1/MetaModel_moex8
          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: 65.35
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Xenon1/MetaModel_moex8
          name: Open LLM Leaderboard

MetaModel_moex8

This model is a Mixure of Experts (MoE) made with mergekit (mixtral branch). It uses the following base models:

🧩 Configuration

dtype: bfloat16
experts:
- positive_prompts:
  - ''
  source_model: gagan3012/MetaModel
- positive_prompts:
  - ''
  source_model: jeonsworld/CarbonVillain-en-10.7B-v2
- positive_prompts:
  - ''
  source_model: jeonsworld/CarbonVillain-en-10.7B-v4
- positive_prompts:
  - ''
  source_model: TomGrc/FusionNet_linear
- positive_prompts:
  - ''
  source_model: DopeorNope/SOLARC-M-10.7B
- positive_prompts:
  - ''
  source_model: VAGOsolutions/SauerkrautLM-SOLAR-Instruct
- positive_prompts:
  - ''
  source_model: upstage/SOLAR-10.7B-Instruct-v1.0
- positive_prompts:
  - ''
  source_model: fblgit/UNA-SOLAR-10.7B-Instruct-v1.0
gate_mode: hidden

💻 Usage

!pip install -qU transformers bitsandbytes accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "gagan3012/MetaModel_moex8"

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

Detailed results can be found here

Metric	Value
Avg.	74.39
AI2 Reasoning Challenge (25-Shot)	71.16
HellaSwag (10-Shot)	88.38
MMLU (5-Shot)	66.29
TruthfulQA (0-shot)	71.91
Winogrande (5-shot)	83.27
GSM8k (5-shot)	65.35