Slim Qa Gen Tiny by llmware

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  Autotrain compatible   Llama   Pytorch   Region:us

Slim Qa Gen 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 Qa Gen Tiny (llmware/slim-qa-gen-tiny)

Slim Qa Gen Tiny Parameters and Internals

Model Type 
text generation, question-answering
Use Cases 
Areas:
research, commercial applications
Additional Notes 
Implements function-calling question generation from a context passage.
Input Output 
Input Format:
`function = "generate"`, `params = "{'question, answer', 'boolean', or 'multiple choice'}"`, `prompt = " " + {text} + "\n" + `<{function}> " + {params} + "" + "\n:"`
Accepted Modalities:
text
Output Format:
Python dictionary e.g., `{'question': [...], 'answer': [...]}`
LLM NameSlim Qa Gen Tiny
Repository ๐Ÿค—https://huggingface.co/llmware/slim-qa-gen-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-qa-gen-tiny.

Rank the Slim Qa Gen 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