BRAG Llama 3.1 8B V0.1 by maximalists

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BRAG Llama 3.1 8B V0.1 Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
BRAG Llama 3.1 8B V0.1 (maximalists/BRAG-Llama-3.1-8b-v0.1)

BRAG Llama 3.1 8B V0.1 Parameters and Internals

Model Type 
Small Language Model (SLM), Retrieval-Augmented Generation (RAG)
Use Cases 
Areas:
RAG tasks with tables and text, Conversational chat
Limitations:
The model is specifically trained for short contexts and may not perform well with longer ones.
Considerations:
To avoid underperformance and potential for hallucinations, please use the recommended system prompt.
Additional Notes 
The model is part of the BRAG series and specifically adapted for RAG tasks.
Supported Languages 
en (Primary language of training and evaluation. Base model has multi-lingual capabilities.)
Input Output 
Input Format:
Message prompt format for using the model.
Accepted Modalities:
text
Performance Tips:
Use the system prompt to enhance performance and reduce hallucinations.
LLM NameBRAG Llama 3.1 8B V0.1
Repository ๐Ÿค—https://huggingface.co/maximalists/BRAG-Llama-3.1-8b-v0.1 
Model Size8b
Required VRAM16.1 GB
Updated2025-01-20
Maintainermaximalists
Model Typellama
Instruction-BasedYes
Model Files  5.0 GB: 1-of-4   5.0 GB: 2-of-4   4.9 GB: 3-of-4   1.2 GB: 4-of-4
Supported Languagesen
Model ArchitectureLlamaForCausalLM
Licensellama3.1
Context Length131072
Model Max Length131072
Transformers Version4.43.1
Tokenizer ClassPreTrainedTokenizerFast
Padding Token<|eot_id|>
Vocabulary Size128256
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than maximalists/BRAG-Llama-3.1-8b-v0.1.

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
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Data Analysis and Insight Generation  
Text Generation  
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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241227