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Meta Llama 3 8B Instruct Fine Tuned by Louis-Dupont

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Meta Llama 3 8B Instruct Fine Tuned is an open-source language model by Louis-Dupont. Features: 8b LLM, VRAM: 18.8GB, Context: 8K, Quantized, Instruction-Based, LLM Explorer Score: 0.14.

  Conversational   Endpoints compatible   F16   Ggml   Gguf   Instruct   Llama   Pytorch   Q4   Quantized   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/Louis-Dupont/Meta-Llama-3-8B-Instruct-fine-tuned 

Meta Llama 3 8B Instruct Fine Tuned Benchmarks

LLME Score: 0.13718
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Meta Llama 3 8B Instruct Fine Tuned (Louis-Dupont/Meta-Llama-3-8B-Instruct-fine-tuned)
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Meta Llama 3 8B Instruct Fine Tuned Parameters and Internals

LLM NameMeta Llama 3 8B Instruct Fine Tuned
Repository 🤗https://huggingface.co/Louis-Dupont/Meta-Llama-3-8B-Instruct-fine-tuned 
Model Size8b
Required VRAM18.8 GB
Updated2026-04-28
MaintainerLouis-Dupont
Model Typellama
Instruction-BasedYes
Model Files  4.9 GB   16.1 GB   4.9 GB: 1-of-7   4.8 GB: 2-of-7   5.0 GB: 3-of-7   5.0 GB: 4-of-7   4.8 GB: 5-of-7   5.0 GB: 6-of-7   2.6 GB: 7-of-7   5.0 GB: 1-of-4   5.0 GB: 2-of-4   5.0 GB: 3-of-4   3.8 GB: 4-of-4
GGML QuantizationYes
GGUF QuantizationYes
Quantization Typeggml|q4|gguf|q4_k
Model ArchitectureLlamaForCausalLM
Context Length8192
Model Max Length8192
Transformers Version4.42.0.dev0
Tokenizer ClassPreTrainedTokenizerFast
Padding Token<|eot_id|>
Vocabulary Size128256
Torch Data Typefloat32

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Note: green Score (e.g. "73.2") means that the model is better than Louis-Dupont/Meta-Llama-3-8B-Instruct-fine-tuned.

Rank the Meta Llama 3 8B Instruct Fine Tuned 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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