Phi 3 Mini 128K Instruct is an open-source language model by microsoft. Features: 3.8b LLM, VRAM: 7.7GB, Context: 128K, License: mit, Instruction-Based, LLM Explorer Score: 0.33, Arc: 63.1, HellaSwag: 80.1, MMLU: 68.7, GSM8K: 69.5.
Phi 3 Mini 128K Instruct Parameters and Internals
Model Type Use Cases
Areas: Research, Commercial applications
Primary Use Cases: Memory/compute constrained environments, Latency bound scenarios, Strong reasoning tasks
Limitations: Not specifically designed or evaluated for all downstream purposes.
Considerations: Adherence to laws and regulations is required.
Additional Notes This is a static model trained on an offline dataset with a cutoff date of October 2023. Future versions may improve upon it.
Supported Languages Training Details
Data Sources: Publicly available documents, Newly created synthetic data, High quality chat format supervised data
Data Volume: Methodology: Supervised fine-tuning, Direct Preference Optimization
Context Length: Training Time: Hardware Used: Model Architecture: Dense decoder-only Transformer
Responsible Ai Considerations
Fairness: Models can over- or under-represent groups, erase representation of some groups, or reinforce stereotypes.
Transparency: Inappropriate or offensive content generation potential.
Accountability: Developers need to ensure the model complies with laws and regulations.
Mitigation Strategies: Use safety classifiers or implement custom safety solutions.
Input Output
Input Format: Accepted Modalities: Output Format: Generated text in response to input
Performance Tips: For certain GPUs, call AutoModelForCausalLM.from_pretrained() with attn_implementation="eager".
Release Notes
Version: Notes: Improvement in long-context understanding, instruction following, reasoning capability.
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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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