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Mixtral Extraction 4x7B Instruct V0.1 by mmnga

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Mixtral Extraction 4x7B Instruct V0.1 is an open-source language model by mmnga. Features: 24.2b LLM, VRAM: 48.5GB, Context: 32K, License: apache-2.0, MoE, Instruction-Based, LLM Explorer Score: 0.11.

  Conversational   De   En   Es   Fr   Instruct   It   Mixtral   Moe   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/mmnga/Mixtral-Extraction-4x7B-Instruct-v0.1 

Mixtral Extraction 4x7B Instruct V0.1 Benchmarks

LLME Score: 0.10684
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Mixtral Extraction 4x7B Instruct V0.1 (mmnga/Mixtral-Extraction-4x7B-Instruct-v0.1)
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Mixtral Extraction 4x7B Instruct V0.1 Parameters and Internals

Model Type 
instruction-following
Additional Notes 
This model is experimental and allows extraction of experts from the base model using bit strings.
Supported Languages 
fr (Proficient), it (Proficient), de (Proficient), es (Proficient), en (Proficient)
Input Output 
Accepted Modalities:
text
LLM NameMixtral Extraction 4x7B Instruct V0.1
Repository 🤗https://huggingface.co/mmnga/Mixtral-Extraction-4x7B-Instruct-v0.1 
Model Size24.2b
Required VRAM48.5 GB
Updated2026-05-26
Maintainermmnga
Model Typemixtral
Instruction-BasedYes
Model Files  4.9 GB: 1-of-10   5.0 GB: 2-of-10   5.0 GB: 3-of-10   4.9 GB: 4-of-10   5.0 GB: 5-of-10   5.0 GB: 6-of-10   5.0 GB: 7-of-10   5.0 GB: 8-of-10   5.0 GB: 9-of-10   3.7 GB: 10-of-10
Supported Languagesfr it de es en
Model ArchitectureMixtralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.37.0.dev0
Tokenizer ClassLlamaTokenizer
Vocabulary Size32000
Torch Data Typefloat16

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Proto Athena 4x7B32K / 48.4 GB70
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...erges MoE 4x7b V10 Mixtralv0.332K / 48.3 GB70
Sixtyoneeighty 4x7B V132K / 48.3 GB660
MixtureofMerges MoE 4x7bRP V1132K / 48.3 GB101
Eclipse Mistral 4x7b32K / 48.5 GB161
West Ramen 7Bx432K / 48.7 GB630
MoE Merging32K / 48.3 GB2680
Boundary Mistral 4x7b MoE32K / 48.7 GB1171
...tral Fusion 4x7B Instruct V0.132K / 48.5 GB1518
Note: green Score (e.g. "73.2") means that the model is better than mmnga/Mixtral-Extraction-4x7B-Instruct-v0.1.

Rank the Mixtral Extraction 4x7B Instruct V0.1 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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