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Mixtral Instruction V0.1 Zh Nf4 by xinping

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Mixtral Instruction V0.1 Zh Nf4 is an open-source language model by xinping. Features: 48.2b LLM, VRAM: 24.5GB, Context: 32K, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.13.

  4-bit   Bitsandbytes   En   Endpoints compatible   Fr   Instruct   Mixtral   Region:us   Safetensors   Sharded   Tensorflow   Zh
Model Card on HF 🤗: https://huggingface.co/xinping/Mixtral-instruction-v0.1_zh-nf4 

Mixtral Instruction V0.1 Zh Nf4 Benchmarks

LLME Score: 0.12736
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Mixtral Instruction V0.1 Zh Nf4 (xinping/Mixtral-instruction-v0.1_zh-nf4)
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Mixtral Instruction V0.1 Zh Nf4 Parameters and Internals

Model Type 
text generation
Additional Notes 
Users should be aware of the risks, biases, and limitations of the model.
Supported Languages 
zh (proficient), en (proficient), fr (proficient)
Input Output 
Input Format:
text
Accepted Modalities:
text
Output Format:
text
LLM NameMixtral Instruction V0.1 Zh Nf4
Repository 🤗https://huggingface.co/xinping/Mixtral-instruction-v0.1_zh-nf4 
Model Size48.2b
Required VRAM24.5 GB
Updated2026-05-16
Maintainerxinping
Model Typemixtral
Instruction-BasedYes
Model Files  5.0 GB: 1-of-5   5.0 GB: 2-of-5   5.0 GB: 3-of-5   5.0 GB: 4-of-5   4.5 GB: 5-of-5
Supported Languageszh en fr
Model ArchitectureMixtralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.38.0
Tokenizer ClassLlamaTokenizer
Padding Token</s>
Vocabulary Size32000
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than xinping/Mixtral-instruction-v0.1_zh-nf4.

Rank the Mixtral Instruction V0.1 Zh Nf4 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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