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Configuration Parsing Warning: In config.json: "quantization_config.bits" must be an integer

Exllamav2 quant (exl2 / 2.5 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:

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)

Vision

llama3_mmproj

image/png

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
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Evaluation results