metadata
language:
- en
license: llama3
tags:
- moe
model-index:
- name: L3-SnowStorm-v1.15-4x8B-B
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: 60.67
name: normalized accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=xxx777xxxASD/L3-SnowStorm-v1.15-4x8B-B
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: 81.6
name: normalized accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=xxx777xxxASD/L3-SnowStorm-v1.15-4x8B-B
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: 68.12
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=xxx777xxxASD/L3-SnowStorm-v1.15-4x8B-B
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: 51.69
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=xxx777xxxASD/L3-SnowStorm-v1.15-4x8B-B
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: 76.56
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=xxx777xxxASD/L3-SnowStorm-v1.15-4x8B-B
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: 69.45
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=xxx777xxxASD/L3-SnowStorm-v1.15-4x8B-B
name: Open LLM Leaderboard
Exllamav2 quant (exl2 / 6.5 bpw) made with ExLlamaV2 v0.1.1
Other EXL2 quants:
Quant | Model Size | lm_head |
---|---|---|
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:
Llama 3 SnowStorm v1.15B 4x8B
base_model: Sao10K_L3-8B-Stheno-v3.1
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
- Nitral-AI/Poppy_Porpoise-1.0-L3-8B
- NeverSleep/Llama-3-Lumimaid-8B-v0.1-OAS
- openlynn/Llama-3-Soliloquy-8B-v2
- Sao10K/L3-8B-Stheno-v3.1
Difference(from SnowStorm v1.0)
- Update from ChaoticNeutrals/Poppy_Porpoise-v0.7-L3-8B to Nitral-AI/Poppy_Porpoise-1.0-L3-8B
- Change base model from NeverSleep/Llama-3-Lumimaid-8B-v0.1-OAS to Sao10K/L3-8B-Stheno-v3.1
Vision
Prompt format: Llama 3
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
Metric | Value |
---|---|
Avg. | 68.01 |
AI2 Reasoning Challenge (25-Shot) | 60.67 |
HellaSwag (10-Shot) | 81.60 |
MMLU (5-Shot) | 68.12 |
TruthfulQA (0-shot) | 51.69 |
Winogrande (5-shot) | 76.56 |
GSM8k (5-shot) | 69.45 |