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TinyAgent 1.1B by squeeze-ai-lab

 »  All LLMs  »  squeeze-ai-lab  »  TinyAgent 1.1B   URL Share it on

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  Autotrain compatible   En   Function calling   Llama   On-device language model   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/squeeze-ai-lab/TinyAgent-1.1B 

TinyAgent 1.1B Benchmarks

LLME Score: 0.19644
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
TinyAgent 1.1B (squeeze-ai-lab/TinyAgent-1.1B)

TinyAgent 1.1B Parameters and Internals

Model Type 
function calling, on-device language model
Use Cases 
Areas:
personal productivity, MacOS applications
Applications:
composing emails, managing contacts, scheduling calendar events, organizing Zoom meetings
Limitations:
irrelevant examples may lead to hallucinations, confusion from unnecessary tool descriptions
Additional Notes 
TinyAgent uses ToolRAG for tool retrieval and example guidance to enhance performance.
Training Details 
Data Sources:
curated real-life use cases dataset, GPT-3.5-Turbo generated instructions, GPT-4-Turbo synthetic execution plans
Data Volume:
40,000 use cases
Methodology:
parameter-efficient fine-tuning with LoRA
Training Time:
3 epochs
LLM NameTinyAgent 1.1B
Repository 🤗https://huggingface.co/squeeze-ai-lab/TinyAgent-1.1B 
Model Size7b
Required VRAM4.4 GB
Updated2025-02-22
Maintainersqueeze-ai-lab
Model Typellama
Model Files  4.4 GB
Supported Languagesen
Model ArchitectureLlamaForCausalLM
Context Length32768
Model Max Length32768
Transformers Version4.40.2
Vocabulary Size32000
Torch Data Typefloat32

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Note: green Score (e.g. "73.2") means that the model is better than squeeze-ai-lab/TinyAgent-1.1B.

Rank the TinyAgent 1.1B 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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