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Mixtral AI TokenClassification Project by LeroyDyer

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Mixtral AI TokenClassification Project is an open-source language model by LeroyDyer. Features: 7.1b LLM, VRAM: 28.4GB, Context: 32K, LLM Explorer Score: 0.12.

  Custom code   En   Endpoints compatible   Mistral   Region:us   Safetensors   Sharded   Tensorflow   Token-classification
Model Card on HF 🤗: https://huggingface.co/LeroyDyer/Mixtral_AI_TokenClassification_Project 

Mixtral AI TokenClassification Project Benchmarks

LLME Score: 0.12219
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Mixtral AI TokenClassification Project (LeroyDyer/Mixtral_AI_TokenClassification_Project)
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Mixtral AI TokenClassification Project Parameters and Internals

Model Type 
token-classification
Additional Notes 
The model includes a token classification head for the Mistral model and can handle various tasks by loading associated heads into the transformer model controller, i.e., automodels. It can intercept inputs or redirect outputs to suit different neural network architectures.
Supported Languages 
en (fluent)
Input Output 
Performance Tips:
Model designed to allow larger contexts and more in-depth prompt sizes, though staying within the window of existing models to avoid increasing GPU costs.
LLM NameMixtral AI TokenClassification Project
Repository 🤗https://huggingface.co/LeroyDyer/Mixtral_AI_TokenClassification_Project 
Model Size7.1b
Required VRAM28.4 GB
Updated2026-07-01
MaintainerLeroyDyer
Model Typemistral
Model Files  5.0 GB: 1-of-6   4.9 GB: 2-of-6   5.0 GB: 3-of-6   5.0 GB: 4-of-6   4.8 GB: 5-of-6   3.7 GB: 6-of-6
Supported Languagesen
Model ArchitectureMistralForCausalLM|MistralForTokenClassification|MistralForCausalThoughtsLM|MistralForQuestionAnswering|MistralForTranslation
Context Length32768
Model Max Length32768
Transformers Version4.38.2
Vocabulary Size32000
Torch Data Typefloat32

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Rank the Mixtral AI TokenClassification Project 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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