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Phi-4-mini-instruct - AI Language Models Tool

Overview

Phi-4-mini-instruct is a 3.8B-parameter lightweight language model from Microsoft, part of the Phi-4 family. It supports a 128K token context and is optimized via supervised fine-tuning and direct preference optimization for instruction-following and reasoning in memory- and compute-constrained, latency-sensitive environments.

Key Features

  • 3.8B-parameter lightweight transformer model
  • Supports up to 128K token context length
  • Optimized for instruction-following and high-quality reasoning
  • Fine-tuned with supervised learning and direct preference optimization
  • Designed for memory- and compute-constrained deployments
  • Built for latency-sensitive inference scenarios

Ideal Use Cases

  • Long-context tasks such as analyzing lengthy documents
  • Latency-sensitive online inference and conversational agents
  • Deployments with tight memory or compute budgets
  • Research on instruction tuning and model behavior
  • Commercial applications requiring reliable instruction-following

Getting Started

  • Visit the model card on Hugging Face to review details and license
  • Download weights or use hosted inference if available
  • Run sample prompts to validate reasoning and instruction-following
  • Measure latency and memory on your target hardware
  • Fine-tune or adapt via supervised or preference-based pipelines if needed

Pricing

Pricing not disclosed in the provided model metadata; check the Hugging Face model page for availability, hosting, and licensing.

Limitations

  • 3.8B-parameter size may underperform larger Phi-4 variants on some complex tasks
  • Model availability, hosting, and license terms must be confirmed on the model page

Key Information

  • Category: Language Models
  • Type: AI Language Models Tool
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