metadata
license: llama3
tags:
- moe
language:
- en
8bpw/h8 exl2 quantization of xxx777xxxASD/L3_SnowStorm_4x8B using exllamav2 0.0.21 and default calibration dataset.
ORIGINAL CARD:
(Maybe i'll change the waifu picture later)
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.
Llama 3 SnowStorm 4x8B
base_model: NeverSleep_Llama-3-Lumimaid-8B-v0.1-OAS
gate_mode: random
dtype: bfloat16
experts_per_token: 2
experts:
- source_model: ChaoticNeutrals_Poppy_Porpoise-v0.7-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
- ChaoticNeutrals/Poppy_Porpoise-v0.7-L3-8B
- NeverSleep/Llama-3-Lumimaid-8B-v0.1-OAS
- openlynn/Llama-3-Soliloquy-8B-v2
- Sao10K/L3-8B-Stheno-v3.1
Difference(from ChaoticSoliloquy v1.5)
- Update from NeverSleep/Llama-3-Lumimaid-8B-v0.1 to NeverSleep/Llama-3-Lumimaid-8B-v0.1-OAS
- Update from openlynn/Llama-3-Soliloquy-8B-v1 to openlynn/Llama-3-Soliloquy-8B-v2
- Update from Sao10K/L3-Solana-8B-v1 to Sao10K/L3-8B-Stheno-v3.1
Vision
