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OpenHermes Mixtral 8x7B 6.0bpw H6 EXL2 by LoneStriker

By LoneStriker · 7 downloads

OpenHermes Mixtral 8x7B 6.0bpw H6 EXL2 is an open-source language model by LoneStriker. Features: LLM, VRAM: 35.3GB, Context: 32K, License: apache-2.0, MoE, Quantized, Instruction-Based, LLM Explorer Score: 0.1.

Base model:finetune:mistralai/... Base model:mistralai/mixtral-8...   Conversational   Distillation   En   Endpoints compatible   Exl2   Finetuned   Gpt4   Instruct   Llama   Mixtral   Moe   Quantized   Region:us   Safetensors   Sharded   Synthetic data   Tensorflow

OpenHermes Mixtral 8x7B 6.0bpw H6 EXL2 Parameters and Internals

Model Type 
Mixtral, Instruct, Finetune
Use Cases 
Areas:
text generation, conversational AI
Considerations:
Designed for multi-turn conversations and setting system prompts
Additional Notes 
Image associated in the documentation may relate to visual branding
Supported Languages 
en (full proficiency)
Training Details 
Data Sources:
OpenHermes dataset
Methodology:
Fine-tuning
Training Time:
3 epochs
Model Architecture:
Based on LLaMA-2
Input Output 
Input Format:
LLaMA-2 prompt template
Accepted Modalities:
text
Output Format:
text
Performance Tips:
Multi-turn conversations and system prompt setups enhance effectiveness
LLM NameOpenHermes Mixtral 8x7B 6.0bpw H6 EXL2
Repository πŸ€—https://huggingface.co/LoneStriker/OpenHermes-Mixtral-8x7B-6.0bpw-h6-exl2 
Base Model(s)  mistralai/Mixtral-8x7B-Instruct-v0.1   mistralai/Mixtral-8x7B-Instruct-v0.1
Required VRAM35.3 GB
Updated2026-08-01
MaintainerLoneStriker
Model Typemixtral
Instruction-BasedYes
Model Files  8.6 GB: 1-of-5   8.6 GB: 2-of-5   8.6 GB: 3-of-5   8.6 GB: 4-of-5   0.9 GB: 5-of-5
Supported Languagesen
Quantization Typeexl2
Model ArchitectureMixtralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.37.0.dev0
Tokenizer ClassLlamaTokenizer
Vocabulary Size32000
Torch Data Typebfloat16

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