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Noromaid V0.4 Mixtral Instruct 8x7b Zloss Bpw350 H6 EXL2 Rpcal by zaq-hack

 »  All LLMs  »  zaq-hack  »  Noromaid V0.4 Mixtral Instruct 8x7b Zloss Bpw350 H6 EXL2 Rpcal   URL Share it on

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  Autotrain compatible   Conversational   Endpoints compatible   Exl2   Instruct   Mixtral   Moe   Quantized   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/zaq-hack/Noromaid-v0.4-Mixtral-Instruct-8x7b-Zloss-bpw350-h6-exl2-rpcal 

Noromaid V0.4 Mixtral Instruct 8x7b Zloss Bpw350 H6 EXL2 Rpcal Benchmarks

LLME Score: 0.13971
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Noromaid V0.4 Mixtral Instruct 8x7b Zloss Bpw350 H6 EXL2 Rpcal (zaq-hack/Noromaid-v0.4-Mixtral-Instruct-8x7b-Zloss-bpw350-h6-exl2-rpcal)
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Noromaid V0.4 Mixtral Instruct 8x7b Zloss Bpw350 H6 EXL2 Rpcal Parameters and Internals

Model Type 
RP, ERP
Use Cases 
Areas:
Research, Commercial Applications
Applications:
Role Playing, Dialog Generation
Additional Notes 
This model is experimental and uses the Chatml prompting format.
Training Details 
Data Sources:
Aesir 1, 2 & 3, LimaRP-20231109, ToxicQAFinal, No-robots-ShareGPT
Model Architecture:
Trained on the Zloss fork of Charles
Input Output 
Input Format:
Chatml prompt format
LLM NameNoromaid V0.4 Mixtral Instruct 8x7b Zloss Bpw350 H6 EXL2 Rpcal
Repository 🤗https://huggingface.co/zaq-hack/Noromaid-v0.4-Mixtral-Instruct-8x7b-Zloss-bpw350-h6-exl2-rpcal 
Required VRAM20.7 GB
Updated2025-09-17
Maintainerzaq-hack
Model Typemixtral
Instruction-BasedYes
Model Files  8.6 GB: 1-of-3   8.6 GB: 2-of-3   3.5 GB: 3-of-3
Quantization Typeexl2
Model ArchitectureMixtralForCausalLM
Licensecc-by-nc-4.0
Context Length32768
Model Max Length32768
Transformers Version4.37.0.dev0
Tokenizer ClassLlamaTokenizer
Vocabulary Size32000
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than zaq-hack/Noromaid-v0.4-Mixtral-Instruct-8x7b-Zloss-bpw350-h6-exl2-rpcal.

Rank the Noromaid V0.4 Mixtral Instruct 8x7b Zloss Bpw350 H6 EXL2 Rpcal Capabilities

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
Censorship and Alignment  
Data Analysis and Insight Generation  
Text Generation  
Text Summarization and Feature Extraction  
Code Generation  
Multi-Language Support and Translation  

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Release v20241124
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