Zoyd/xxx777xxxASD_L3_SnowStorm_4x8B-8_0bpw_exl2
Exllamav2 quant (exl2 / 8.0 bpw) made with ExLlamaV2 v0.0.21
Other EXL2 quants: | Quant | Model Size | lm_head | | ----- | ---------- | ------- | |<center>[2.2](https://huggingface.co/Zoyd/xxx777xxxASD_L3_SnowStorm_4x8B-2_2bpw_exl2)</center> | <center>7777 MB</center> | <center>6</center> | |<center>[2.5](https://huggingface.co/Zoyd/xxx777xxxASD_L3_SnowStorm_4x8B-2_5bpw_exl2)</center> | <center>8519 MB</center> | <center>6</center> | |<center>[3.0](https://huggingface.co/Zoyd/xxx777xxxASD_L3_SnowStorm_4x8B-3_0bpw_exl2)</center> | <center>9944 MB</center> | <center>6</center> | |<center>[3.5](https://huggingface.co/Zoyd/xxx777xxxASD_L3_SnowStorm_4x8B-3_5bpw_exl2)</center> | <center>11365 MB</center> | <center>6</center> | |<center>[3.75](https://huggingface.co/Zoyd/xxx777xxxASD_L3_SnowStorm_4x8B-3_75bpw_exl2)</center> | <center>12080 MB</center> | <center>6</center> | |<center>[4.0](https://huggingface.co/Zoyd/xxx777xxxASD_L3_SnowStorm_4x8B-4_0bpw_exl2)</center> | <center>12789 MB</center> | <center>6</center> | |<center>[4.25](https://huggingface.co/Zoyd/xxx777xxxASD_L3_SnowStorm_4x8B-4_25bpw_exl2)</center> | <center>13503 MB</center> | <center>6</center> | |<center>[5.0](https://huggingface.co/Zoyd/xxx777xxxASD_L3_SnowStorm_4x8B-5_0bpw_exl2)</center> | <center>15632 MB</center> | <center>6</center> | |<center>[6.0](https://huggingface.co/Zoyd/xxx777xxxASD_L3_SnowStorm_4x8B-6_0bpw_exl2)</center> | <center>18594 MB</center> | <center>8</center> | |<center>[6.5](https://huggingface.co/Zoyd/xxx777xxxASD_L3_SnowStorm_4x8B-6_5bpw_exl2)</center> | <center>19969 MB</center> | <center>8</center> | |<center>[8.0](https://huggingface.co/Zoyd/xxx777xxxASD_L3_SnowStorm_4x8B-8_0bpw_exl2)</center> | <center>24115 MB</center> | <center>8</center> |
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<div class="image-container"> <img src="https://cdn-uploads.huggingface.co/production/uploads/64f5e51289c121cb864ba464/OuMe79ZQPdCX01rTdfgXn.png" style="width: 96%; margin: auto;" > </div>
(Maybe i'll change the waifu picture later)
[!NOTE] GGUF/Exl2 quants
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-v3.1Models 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

