metadata

license: apache-2.0
datasets:
  - irlab-udc/alpaca_data_galician
language:
  - gl
  - en

Galician Fine-Tuned LLM Model

This repository contains a large language model (LLM) fine-tuned using the LLaMA Factory library and the Finisterrae III supercomputer at CESGA. The base model used for fine-tuning was Meta's LLaMA 3.

Model Description

This LLM model has been specifically fine-tuned to understand and generate text in Galician. It was fine-tuned using a modified version of the irlab-udc/alpaca_data_galician dataset, enriched with synthetic data to enhance its text generation and comprehension capabilities in specific contexts.

Technical Details

Base Model: Meta's LLaMA 3
Fine-Tuning Platform: LLaMA Factory
Infrastructure: Finisterrae III, CESGA
Dataset: irlab-udc/alpaca_data_galician (with modifications)
Fine-Tuning Objective: To improve text comprehension and generation in Galician.

How to Use the Model

To use this model, follow the example code provided below. Ensure you have the necessary libraries installed (e.g., Hugging Face's transformers).

Installation

pip install transformers

Installation

from transformers import AutoModelForCausalLM, AutoTokenizer

model_name = "abrahammg/Llama3-8B-Galician-Chat"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)

text = "Enter some text in Galician here."
inputs = tokenizer(text, return_tensors="pt")
outputs = model.generate(**inputs)

print(tokenizer.decode(outputs[0], skip_special_tokens=True))