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Mixtral 8x22B V0.1 AWQ by mistral-community

 »  All LLMs  »  mistral-community  »  Mixtral 8x22B V0.1 AWQ   URL Share it on

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  4-bit   Autotrain compatible   Awq Base model:quantized:v2ray/mix... Base model:v2ray/mixtral-8x22b...   De   En   Endpoints compatible   Es   Fr   It   Mixtral   Moe   Quantized   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/mistral-community/Mixtral-8x22B-v0.1-AWQ 

Mixtral 8x22B V0.1 AWQ Benchmarks

LLME Score: 0.22647
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Mixtral 8x22B V0.1 AWQ (mistral-community/Mixtral-8x22B-v0.1-AWQ)

Mixtral 8x22B V0.1 AWQ Parameters and Internals

Model Type 
text-generation, quantized
Additional Notes 
The model supports inference via quantized (AWQ) format. The quantization was performed by MaziyarPanahi to allow more efficient inference.
Supported Languages 
en (high), es (high), de (high), it (high), fr (high)
Training Details 
Context Length:
65000
Model Architecture:
176B MoE with ~40B active
Input Output 
Accepted Modalities:
text
LLM NameMixtral 8x22B V0.1 AWQ
Repository 🤗https://huggingface.co/mistral-community/Mixtral-8x22B-v0.1-AWQ 
Model NameMixtral-8x22B-v0.1-AWQ
Model Creatorv2ray
Base Model(s)  v2ray/Mixtral-8x22B-v0.1   v2ray/Mixtral-8x22B-v0.1
Model Size19.2b
Required VRAM73.7 GB
Updated2025-01-20
Maintainermistral-community
Model Typemixtral
Model Files  5.0 GB: 1-of-15   5.0 GB: 2-of-15   5.0 GB: 3-of-15   5.0 GB: 4-of-15   5.0 GB: 5-of-15   5.0 GB: 6-of-15   5.0 GB: 7-of-15   5.0 GB: 8-of-15   5.0 GB: 9-of-15   5.0 GB: 10-of-15   5.0 GB: 11-of-15   5.0 GB: 12-of-15   5.0 GB: 13-of-15   5.0 GB: 14-of-15   3.7 GB: 15-of-15
Supported Languagesen es de it fr
AWQ QuantizationYes
Quantization Typeawq
Model ArchitectureMixtralForCausalLM
Context Length65536
Model Max Length65536
Transformers Version4.38.2
Tokenizer ClassLlamaTokenizer
Vocabulary Size32000
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than mistral-community/Mixtral-8x22B-v0.1-AWQ.

Rank the Mixtral 8x22B V0.1 AWQ 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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Release v20241227
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