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TinyLlama RAG by TroyDoesAI

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  Autotrain compatible   Conversational   Endpoints compatible   Llama   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/TroyDoesAI/TinyLlama-RAG 

TinyLlama RAG Benchmarks

LLME Score: 0.19181
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
TinyLlama RAG (TroyDoesAI/TinyLlama-RAG)

TinyLlama RAG Parameters and Internals

Model Type 
contextual prompt-response
Use Cases 
Areas:
Research and Development, Prototyping
Applications:
Contextual applications, RAG applications
Primary Use Cases:
Enhancing adherence to context, Reducing hallucinations
Limitations:
Limited ability to say no, Might struggle with certain queries due to model size limitations
Additional Notes 
Uses contextual prompts to improve response accuracy and link specific sources.
Input Output 
Input Format:
Contextual-Request format with explicit delimiters to denote input, context, and instructions.
Accepted Modalities:
text
Output Format:
Contextual response including source references as indicated in the input context.
Performance Tips:
Using explicit delimiters helps the model understand input boundaries better.
LLM NameTinyLlama RAG
Repository 🤗https://huggingface.co/TroyDoesAI/TinyLlama-RAG 
Model Size1.1b
Required VRAM2.2 GB
Updated2025-02-22
MaintainerTroyDoesAI
Model Typellama
Model Files  2.2 GB
Model ArchitectureLlamaForCausalLM
Licensecc-by-nc-nd-4.0
Context Length2048
Model Max Length2048
Transformers Version4.39.3
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 TroyDoesAI/TinyLlama-RAG.

Rank the TinyLlama RAG 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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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241227
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