Phi 3.5 Instruct Vul by abhinav2024

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  4bit   Conversational   En   Endpoints compatible   Instruct   Llama   Pytorch   Quantized   Region:us   Sharded   Trl   Unsloth

Phi 3.5 Instruct Vul Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Phi 3.5 Instruct Vul (abhinav2024/phi-3.5-instruct-vul)
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Phi 3.5 Instruct Vul Parameters and Internals

Model Type 
text-generation-inference
Additional Notes 
This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.
Supported Languages 
en (fluent)
LLM NamePhi 3.5 Instruct Vul
Repository ๐Ÿค—https://huggingface.co/abhinav2024/phi-3.5-instruct-vul 
Base Model(s)  unsloth/phi-3.5-mini-instruct-bnb-4bit   unsloth/phi-3.5-mini-instruct-bnb-4bit
Required VRAM7.6 GB
Updated2026-01-11
Maintainerabhinav2024
Model Typellama
Instruction-BasedYes
Model Files  5.0 GB: 1-of-2   2.6 GB: 2-of-2
Supported Languagesen
Quantization Type4bit
Model ArchitectureLlamaForCausalLM
Licenseapache-2.0
Context Length131072
Model Max Length131072
Transformers Version4.44.2
Tokenizer ClassLlamaTokenizer
Padding Token<|placeholder6|>
Vocabulary Size32064
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than abhinav2024/phi-3.5-instruct-vul.

Rank the Phi 3.5 Instruct Vul 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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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241124