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Mistral 7B Instruct V0.2 2x7B MoE 6.0bpw H6 EXL2 by Nexesenex

 »  All LLMs  »  Nexesenex  »  Mistral 7B Instruct V0.2 2x7B MoE 6.0bpw H6 EXL2   URL Share it on

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Mistral 7B Instruct V0.2 2x7B MoE 6.0bpw H6 EXL2 is an open-source language model by Nexesenex. Features: 7b LLM, VRAM: 9.9GB, Context: 32K, License: apache-2.0, MoE, Quantized, Fine-Tuned, Instruction-Based, Merged, LLM Explorer Score: 0.11.

  Merged Model   Arxiv:2310.06825   Conversational   Exl2   Finetuned   Instruct   Mixtral   Moe   Quantized   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/Nexesenex/Mistral-7B-Instruct-v0.2-2x7B-MoE-6.0bpw-h6-exl2 

Mistral 7B Instruct V0.2 2x7B MoE 6.0bpw H6 EXL2 Benchmarks

LLME Score: 0.1082
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Mistral 7B Instruct V0.2 2x7B MoE 6.0bpw H6 EXL2 (Nexesenex/Mistral-7B-Instruct-v0.2-2x7B-MoE-6.0bpw-h6-exl2)
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Mistral 7B Instruct V0.2 2x7B MoE 6.0bpw H6 EXL2 Parameters and Internals

Model Type 
text generation, instruction fine-tuned
Use Cases 
Limitations:
The model does not have any moderation mechanisms., It's a quick demonstration; improvements are expected in future iterations.
Training Details 
Methodology:
Instruction fine-tuning
Model Architecture:
Transformer model with Grouped-Query Attention, Sliding-Window Attention, and Byte-fallback BPE tokenizer
Input Output 
Input Format:
Use `[INST]` and `[/INST]` tokens to enclose instructions.
LLM NameMistral 7B Instruct V0.2 2x7B MoE 6.0bpw H6 EXL2
Repository 🤗https://huggingface.co/Nexesenex/Mistral-7B-Instruct-v0.2-2x7B-MoE-6.0bpw-h6-exl2 
Merged ModelYes
Model Size7b
Required VRAM9.9 GB
Updated2026-05-23
MaintainerNexesenex
Model Typemixtral
Instruction-BasedYes
Model Files  8.6 GB: 1-of-2   1.3 GB: 2-of-2
Quantization Typeexl2
Model ArchitectureMixtralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.37.0.dev0
Tokenizer ClassLlamaTokenizer
Padding Token<s>
Vocabulary Size32000
Torch Data Typefloat16

Best Alternatives to Mistral 7B Instruct V0.2 2x7B MoE 6.0bpw H6 EXL2

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Context / RAM
Downloads
Likes
Mini Mixtral V0.232K / 25.8 GB30614
OpenMistral MoE32K / 48.3 GB12180
Multilingual Mistral32K / 93.5 GB1252
FNCARL900032K / 48.3 GB430
Magiq 332K / 37.1 GB73
Bigstral 12B 32K 8xMoE32K / 163.3 GB122
CollAIborate4x7B32K / 48.7 GB51
CollAIborate4x7B32K / 48.7 GB11
OpenMistral MoE32K / 48.3 GB70
Note: green Score (e.g. "73.2") means that the model is better than Nexesenex/Mistral-7B-Instruct-v0.2-2x7B-MoE-6.0bpw-h6-exl2.

Rank the Mistral 7B Instruct V0.2 2x7B MoE 6.0bpw H6 EXL2 Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

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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