poem writing, email drafting, story creation, text summarization, Python code generation
Limitations:
produces incorrect code snippets and statements, to be treated as suggestions, not fine-tuned for instructions, language limitations to standard English only
Considerations:
For research purposes; not suggested for direct adoption in production
Additional Notes
Trained with selected safe data, but still vulnerable to producing harmful content.
Supported Languages
en (standard English)
Training Details
Data Sources:
same sources used for phi-1, with additional NLP synthetic texts
Data Volume:
150 billion tokens
Training Time:
8 days
Hardware Used:
32xA100-40G GPUs
Model Architecture:
Transformer with next-word prediction objective
Input Output
Input Format:
QA, chat, and code formats
Accepted Modalities:
text
Output Format:
QA, chat, and code formats
Performance Tips:
Use FP16 / CUDA for optimal performance
Release Notes
Version:
initial
Notes:
Model provides near state-of-the-art performance in language tasks for its parameter size, not fine-tuned for instructions.
Note: green Score (e.g. "73.2") means that the model is better than TKDKid1000/phi-1_5-GGUF.
Rank the Phi 1 5 GGUF 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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