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ChaoticSoliloquy 4x8B 6bpw H6 EXL2 by JayhC

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Model Card on HF 🤗: https://huggingface.co/JayhC/ChaoticSoliloquy-4x8B-6bpw-h6-exl2 

ChaoticSoliloquy 4x8B 6bpw H6 EXL2 Benchmarks

LLME Score: 0.18384
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
ChaoticSoliloquy 4x8B 6bpw H6 EXL2 (JayhC/ChaoticSoliloquy-4x8B-6bpw-h6-exl2)

ChaoticSoliloquy 4x8B 6bpw H6 EXL2 Parameters and Internals

Model Type 
Mixture of Experts, RP-oriented
Use Cases 
Primary Use Cases:
RP/ERP tasks
Supported Languages 
en (high)
Training Details 
Methodology:
exl2 quantization of ChaoticSoliloquy-4x8B using default exllamav2 calibration dataset
Model Architecture:
MoE with gate_mode random, dtype bfloat16, experts_per_token 2
Input Output 
Input Format:
Llama 3
LLM NameChaoticSoliloquy 4x8B 6bpw H6 EXL2
Repository 🤗https://huggingface.co/JayhC/ChaoticSoliloquy-4x8B-6bpw-h6-exl2 
Model Size8b
Required VRAM19.4 GB
Updated2025-02-05
MaintainerJayhC
Model Typemixtral
Model Files  8.6 GB: 1-of-3   8.6 GB: 2-of-3   2.2 GB: 3-of-3
Supported Languagesen
Quantization Typeexl2
Model ArchitectureMixtralForCausalLM
Licensellama3
Context Length8192
Model Max Length8192
Transformers Version4.37.2
Tokenizer ClassPreTrainedTokenizerFast
Padding Token<|begin_of_text|>
Vocabulary Size128256
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than JayhC/ChaoticSoliloquy-4x8B-6bpw-h6-exl2.

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Release v20241227
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