saishshinde15/Summmary_Model_Llama-3.2-1B-Instruct

🌟 Summarization Model Card 🌟

Model Overview

• —Model Name: Llama-3.2-1B Instruct Model Fine-tuned for Summarization
• —Developed by: saishshinde15
• —License: Apache-2.0
• —Base Model: meta-llama/Llama-3.2-1B-Instruct

Description

This model has been fine-tuned to excel in generating concise and informative summaries from lengthy texts. It captures key ideas while presenting them in an easy-to-read bullet-point format.

Key Features

• —Language: English
• —Fine-tuned on: The dataset openai/summarize_from_feedback for improved summarization capabilities.
• —Performance Metric: Evaluated based on accuracy.

Prompt for Optimal Use

For the best results, please utilize the following tried-and-true prompt structure:

You are given the following text. Please provide a summary in 5-10 key points, depending on the length of the document. Each point should be clearly formatted in bullet format, starting with an asterisk (*).

**Note:** The examples provided below are for your reference only and should not be included in your response.

### Examples (for reference only):
* The sky is blue on a clear day.
* Water boils at 100 degrees Celsius.
* Trees produce oxygen through photosynthesis.

### Original Text:
{}

### Key Points Summary (in bullet points):



# Model Loading Instructions

To load this model, use the following code snippet:

from peft import AutoPeftModelForCausalLM from transformers import AutoTokenizer

Replace "lora_model" with your actual model name

model = AutoPeftModelForCausalLM.frompretrained( "saishshinde15/SummmaryModelLlama-3.2-1B-Instruct", # YOUR MODEL YOU USED FOR TRAINING loadin4bit=True, # Adjust as needed ) tokenizer = AutoTokenizer.frompretrained("saishshinde15/SummmaryModelLlama-3.2-1B-Instruct")