Slim Summary Tiny by llmware

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  Autotrain compatible   Llama   Pytorch   Region:us

Slim Summary Tiny Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Slim Summary Tiny (llmware/slim-summary-tiny)

Slim Summary Tiny Parameters and Internals

Model Type 
text summarization
Additional Notes 
The model is specialized for function-call summarization with an optional list size parameter. Model can run on CPUs.
Input Output 
Input Format:
text passage
Accepted Modalities:
text
Output Format:
python list of distinct summary points
Performance Tips:
Use 'quantized tool' version for fast inference. Use provided string remediation handler from llmware to handle conversion issues. Adjust parameters for specific use cases, e.g. 'brief description (1)' for a single output point.
LLM NameSlim Summary Tiny
Repository ๐Ÿค—https://huggingface.co/llmware/slim-summary-tiny 
Model Size1.1b
Required VRAM2.2 GB
Updated2025-02-22
Maintainerllmware
Model Typellama
Model Files  2.2 GB
Model ArchitectureLlamaForCausalLM
Licenseapache-2.0
Context Length2048
Model Max Length2048
Transformers Version4.38.1
Beginning of Sentence Token<s>
End of Sentence Token</s>
Unk Token<unk>
Vocabulary Size32000
Torch Data Typefloat32

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Note: green Score (e.g. "73.2") means that the model is better than llmware/slim-summary-tiny.

Rank the Slim Summary Tiny Capabilities

๐Ÿ†˜ 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! ๐ŸŒŸ

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