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TinyLlama V1.1 Agent Rag Nerd V1 by Josephgflowers

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  Autotrain compatible   Conversational   Endpoints compatible   Llama   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/Josephgflowers/TinyLlama-v1.1-Agent-Rag-Nerd-v1 

TinyLlama V1.1 Agent Rag Nerd V1 Benchmarks

LLME Score: 0.19565
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
TinyLlama V1.1 Agent Rag Nerd V1 (Josephgflowers/TinyLlama-v1.1-Agent-Rag-Nerd-v1)

TinyLlama V1.1 Agent Rag Nerd V1 Parameters and Internals

Additional Notes 
Special Thanks to https://nationtech.io/ for their generous sponsorship in training this model.
Training Details 
Data Sources:
Agent based dataset of tool usage, function calling, programming, STEM data, NER data, address parsing, RAG, summary
Methodology:
Fine-tuning
LLM NameTinyLlama V1.1 Agent Rag Nerd V1
Repository 🤗https://huggingface.co/Josephgflowers/TinyLlama-v1.1-Agent-Rag-Nerd-v1 
Model Size1.1b
Required VRAM2.2 GB
Updated2025-02-22
MaintainerJosephgflowers
Model Typellama
Model Files  2.2 GB
Model ArchitectureLlamaForCausalLM
Licensemit
Context Length2048
Model Max Length2048
Transformers Version4.41.1
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 Josephgflowers/TinyLlama-v1.1-Agent-Rag-Nerd-v1.

Rank the TinyLlama V1.1 Agent Rag Nerd V1 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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Release v20241227
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