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Slim Q Gen Phi 3 by llmware

 »  All LLMs  »  llmware  »  Slim Q Gen Phi 3   URL Share it on

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  Autotrain compatible   Conversational   Custom code   Instruct   Phi3   Pytorch   Region:us
Model Card on HF 🤗: https://huggingface.co/llmware/slim-q-gen-phi-3 

Slim Q Gen Phi 3 Benchmarks

LLME Score: 0.19482
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Slim Q Gen Phi 3 (llmware/slim-q-gen-phi-3)

Slim Q Gen Phi 3 Parameters and Internals

Model Type 
specialized function-calling question generation
Additional Notes 
For fast inference use, the 'quantized tool' version, 'slim-q-gen-phi-3-tool', is recommended.
Input Output 
Input Format:
function = "generate" params = "{'question', 'boolean', or 'multiple choice'}" prompt = " " + {text} + "\n" + "<{ unction}> " + {params} + "" + "\n:"
Output Format:
Output in the form of a Python dictionary.
LLM NameSlim Q Gen Phi 3
Repository 🤗https://huggingface.co/llmware/slim-q-gen-phi-3 
Required VRAM7.6 GB
Updated2025-02-22
Maintainerllmware
Model Typephi3
Instruction-BasedYes
Model Files  7.6 GB
Model ArchitecturePhi3ForCausalLM
Licenseapache-2.0
Context Length4096
Model Max Length4096
Transformers Version4.38.1
Padding Token<|endoftext|>
Vocabulary Size32064
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than llmware/slim-q-gen-phi-3.

Rank the Slim Q Gen Phi 3 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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