metadata

language: en
tags:
  - llama
  - Peft
  - fine-tuning
  - text-generation
  - causal-lm
  - NLP
license: mit
datasets:
  - mlabonne/FineTome-100k

Llama-3.2-3b-FineTome-100k

Model Description

Llama-3.2-3b-FineTome-100k is a fine-tuned version of the Llama 3.2 model, optimized for various natural language processing (NLP) tasks. It has been trained on a dataset containing 100,000 examples, designed to improve its performance on domain-specific applications.

Key Features

Model Size: 3 billion parameters
Architecture: Transformer-based architecture optimized for NLP tasks
Fine-tuning Dataset: 100k curated examples from diverse sources

Use Cases

Text generation
Sentiment analysis
Question answering
Language translation
Dialogue systems

Installation

To use the Llama-3.2-3b-FineTome-100k model, ensure you have the transformers library installed. You can install it using pip:

pip install transformers

from transformers import AutoTokenizer, AutoModelForCausalLM

# Load the tokenizer and model
tokenizer = AutoTokenizer.from_pretrained("khushwant04/Llama-3.2-3b-FineTome-100k")
model = AutoModelForCausalLM.from_pretrained("khushwant04/Llama-3.2-3b-FineTome-100k")

# Encode input text
input_text = "Tell me someting intresting about India and its culture?"
input_ids = tokenizer.encode(input_text, return_tensors='pt')

# Generate output
output = model.generate(input_ids, max_length=50)
output_text = tokenizer.decode(output[0], skip_special_tokens=True)

print(output_text)