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sinda1/
phi_3_5

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Phi 3.5 Mini Instruct

This repository hosts the Phi 3.5 Mini Instruct model, a fine-tuned version of the Phi-3.5 base model. It is optimized for instruction-following tasks and supports various downstream applications, such as question answering, summarization, and chatbot interactions.

Model Overview

Base Model: Phi-3.5-mini-instruct
Fine-Tuning Framework: LoRA (Low-Rank Adaptation)
Quantization: 4-bit quantized for efficient inference
Sequence Length: Supports sequences up to 2048 tokens
Training Dataset: Alpaca-style instruction-following dataset

Features

Optimized for instruction-following and conversational tasks
Lightweight model leveraging 4-bit quantization
Supports extended contexts via RoPE scaling (2048 tokens)

Intended Use

Applications

Conversational AI: Develop chatbots for natural and engaging interactions
Text Summarization: Generate concise summaries of input texts
Question Answering: Provide accurate answers based on given context
Instruction Following: Perform tasks based on detailed instructions

Limitations

The model may not perform well on tasks requiring knowledge outside its training data.
Outputs should be validated in critical applications, such as healthcare or legal advice.

Usage

Installation

To use this model, first install the necessary dependencies:

pip install transformers accelerate

sinda1/phi_3_5