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Nous Hermes 2 Mixtral 8x7B DPO 5.0bpw H6 EXL2 by LoneStriker

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Nous Hermes 2 Mixtral 8x7B DPO 5.0bpw H6 EXL2 is an open-source language model by LoneStriker. Features: LLM, VRAM: 29.5GB, Context: 32K, License: apache-2.0, MoE, Quantized, LLM Explorer Score: 0.11.

Base model:finetune:mistralai/... Base model:mistralai/mixtral-8...   Chatml   Conversational   Distillation   Dpo   En   Endpoints compatible   Exl2   Finetuned   Gpt4   Instruct   Mixtral   Moe   Quantized   Region:us   Rlhf   Safetensors   Sharded   Synthetic data   Tensorflow
Model Card on HF 🤗: https://huggingface.co/LoneStriker/Nous-Hermes-2-Mixtral-8x7B-DPO-5.0bpw-h6-exl2 

Nous Hermes 2 Mixtral 8x7B DPO 5.0bpw H6 EXL2 Benchmarks

LLME Score: 0.11327
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Nous Hermes 2 Mixtral 8x7B DPO 5.0bpw H6 EXL2 (LoneStriker/Nous-Hermes-2-Mixtral-8x7B-DPO-5.0bpw-h6-exl2)
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Nous Hermes 2 Mixtral 8x7B DPO 5.0bpw H6 EXL2 Parameters and Internals

Model Type 
instruct, finetune, chatml, DPO, RLHF, gpt4, synthetic data, distillation
Additional Notes 
The model was developed using sponsorship from Together.ai.
Supported Languages 
en (Proficient)
Training Details 
Data Sources:
GPT-4 generated data, Other high quality open datasets
Data Volume:
1,000,000+ entries
Methodology:
SFT + DPO
Hardware Used:
Sponsored by Together.ai
Input Output 
Input Format:
ChatML with roles for turns and system prompt capability.
Accepted Modalities:
text
Output Format:
Text in chat dialogue format with roles and turns.
Performance Tips:
Ensure to use the ChatML format to guide interaction with appropriate messages and responses.
LLM NameNous Hermes 2 Mixtral 8x7B DPO 5.0bpw H6 EXL2
Repository 🤗https://huggingface.co/LoneStriker/Nous-Hermes-2-Mixtral-8x7B-DPO-5.0bpw-h6-exl2 
Base Model(s)  mistralai/Mixtral-8x7B-v0.1   mistralai/Mixtral-8x7B-v0.1
Required VRAM29.5 GB
Updated2026-04-25
MaintainerLoneStriker
Model Typemixtral
Model Files  8.6 GB: 1-of-4   8.6 GB: 2-of-4   8.6 GB: 3-of-4   3.7 GB: 4-of-4
Supported Languagesen
Quantization Typeexl2
Model ArchitectureMixtralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.37.0.dev0
Tokenizer ClassLlamaTokenizer
Padding Token</s>
Vocabulary Size32002
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than LoneStriker/Nous-Hermes-2-Mixtral-8x7B-DPO-5.0bpw-h6-exl2.

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Instruction Following and Task Automation  
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