metadata

language:
  - en
license: llama3
tags:
  - moe
model-index:
  - name: L3-SnowStorm-v1.15-4x8B-A
    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: 62.2
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=xxx777xxxASD/L3-SnowStorm-v1.15-4x8B-A
          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: 81.09
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=xxx777xxxASD/L3-SnowStorm-v1.15-4x8B-A
          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: 67.89
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=xxx777xxxASD/L3-SnowStorm-v1.15-4x8B-A
          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: 52.11
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=xxx777xxxASD/L3-SnowStorm-v1.15-4x8B-A
          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: 76.32
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=xxx777xxxASD/L3-SnowStorm-v1.15-4x8B-A
          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: 66.49
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=xxx777xxxASD/L3-SnowStorm-v1.15-4x8B-A
          name: Open LLM Leaderboard

Exllamav2 quant (exl2 / 6.0 bpw) made with ExLlamaV2 v0.1.1

Other EXL2 quants:

Quant	Model Size	lm_head
2.2	7777 MB	6
2.5	8520 MB	6
3.0	9941 MB	6
3.5	11366 MB	6
3.75	12066 MB	6
4.0	12789 MB	6
4.25	13504 MB	6
5.0	15640 MB	6
6.0	18586 MB	8
6.5	20007 MB	8
8.0	24101 MB	8

GGUF

Experimental RP-oriented MoE, the idea was to get a model that would be equal to or better than Mixtral 8x7B and it's finetunes in RP/ERP tasks.

There's:

v1.15A <- You're here
v1.15B

Llama 3 SnowStorm v1.15A 4x8B

base_model: NeverSleep_Llama-3-Lumimaid-8B-v0.1-OAS
gate_mode: random
dtype: bfloat16
experts_per_token: 2
experts:
  - source_model: Nitral-AI_Poppy_Porpoise-1.0-L3-8B
  - source_model: NeverSleep_Llama-3-Lumimaid-8B-v0.1-OAS
  - source_model: openlynn_Llama-3-Soliloquy-8B-v2
  - source_model: Sao10K_L3-8B-Stheno-v3.1

Models used

Difference(from SnowStorm v1.0)

Update from ChaoticNeutrals/Poppy_Porpoise-v0.7-L3-8B to Nitral-AI/Poppy_Porpoise-0.85-L3-8B

Vision

llama3_mmproj

Prompt format: Llama 3

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	67.68
AI2 Reasoning Challenge (25-Shot)	62.20
HellaSwag (10-Shot)	81.09
MMLU (5-Shot)	67.89
TruthfulQA (0-shot)	52.11
Winogrande (5-shot)	76.32
GSM8k (5-shot)	66.49