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Mixtral 8x22B Instruct V0.1 4bit by prince-canuma

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Model Card on HF 🤗: https://huggingface.co/prince-canuma/Mixtral-8x22B-Instruct-v0.1-4bit 

Mixtral 8x22B Instruct V0.1 4bit Benchmarks

LLME Score: 0.18179
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Mixtral 8x22B Instruct V0.1 4bit (prince-canuma/Mixtral-8x22B-Instruct-v0.1-4bit)

Mixtral 8x22B Instruct V0.1 4bit Parameters and Internals

Model Type 
Sparse Mixture of Experts, Pretrained Generative LLM
Use Cases 
Limitations:
No moderation mechanisms, Requires moderated outputs in certain environments
Additional Notes 
Weights compatible with vLLM and Hugging Face Transformers, not instantiable with HF yet.
Supported Languages 
fr (Supported), it (Supported), de (Supported), es (Supported), en (Supported)
Input Output 
Input Format:
[INST] Instruction [/INST]
Accepted Modalities:
Text
Output Format:
Model answer with a possible follow-up instruction enclosed in [INST] tags
Performance Tips:
Ensure strict adherence to the instruction format for optimal outputs.
LLM NameMixtral 8x22B Instruct V0.1 4bit
Repository 🤗https://huggingface.co/prince-canuma/Mixtral-8x22B-Instruct-v0.1-4bit 
Model Size72.7b
Required VRAM80.2 GB
Updated2025-02-05
Maintainerprince-canuma
Model Typemixtral
Instruction-BasedYes
Model Files  5.0 GB: 1-of-17   5.0 GB: 2-of-17   5.0 GB: 3-of-17   5.0 GB: 4-of-17   5.0 GB: 5-of-17   5.0 GB: 6-of-17   5.0 GB: 7-of-17   5.0 GB: 8-of-17   5.0 GB: 9-of-17   5.0 GB: 10-of-17   5.0 GB: 11-of-17   5.0 GB: 12-of-17   5.0 GB: 13-of-17   5.0 GB: 14-of-17   5.0 GB: 15-of-17   4.8 GB: 16-of-17   0.4 GB: 17-of-17
Supported Languagesfr it de es en
Quantization Type4bit
Model ArchitectureMixtralForCausalLM
Licenseapache-2.0
Context Length65536
Model Max Length65536
Transformers Version4.39.3
Tokenizer ClassLlamaTokenizer
Vocabulary Size32768
Torch Data Typefloat16

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...xtral 8x22B Instruct V0.1 4bit64K / 80.2 GB29511
Note: green Score (e.g. "73.2") means that the model is better than prince-canuma/Mixtral-8x22B-Instruct-v0.1-4bit.

Rank the Mixtral 8x22B Instruct V0.1 4bit Capabilities

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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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