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Medicinal QnA Phi2 Custom by YuvrajSingh9886

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  Autotrain compatible   Instruct   Phi   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/YuvrajSingh9886/medicinal-QnA-phi2-custom 

Medicinal QnA Phi2 Custom Benchmarks

LLME Score: 0.15482
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Medicinal QnA Phi2 Custom (YuvrajSingh9886/medicinal-QnA-phi2-custom)
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Medicinal QnA Phi2 Custom Parameters and Internals

Model Type 
Text Generation, Question-Answering
Use Cases 
Areas:
Health Counseling Chatbot development
Additional Notes 
The model has undergone changes to the generation_config file for better performance.
Training Details 
Data Sources:
Amod/mental_health_counseling_conversations
Methodology:
QLoRA was used for quantization purposes.
Hardware Used:
(1) RTX 4090 (24GB VRAM), 48GB 8vCPU (RAM)
Model Architecture:
Phi-2 model with BitsAndBytes support
LLM NameMedicinal QnA Phi2 Custom
Repository 🤗https://huggingface.co/YuvrajSingh9886/medicinal-QnA-phi2-custom 
Model Size2.8b
Required VRAM5.6 GB
Updated2025-09-23
MaintainerYuvrajSingh9886
Model Typephi
Model Files  5.0 GB: 1-of-2   0.6 GB: 2-of-2
Model ArchitecturePhiForCausalLM
Context Length2048
Model Max Length2048
Transformers Version4.41.2
Tokenizer ClassCodeGenTokenizer
Vocabulary Size51200
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than YuvrajSingh9886/medicinal-QnA-phi2-custom.

Rank the Medicinal QnA Phi2 Custom 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
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