The GPT-Neo Small Portuguese model is a fine-tuned version of GPT-Neo 125M developed by EleutherAI specifically for the Portuguese language. In this blog, we’ll walk you through how to set it up and generate text using this amazing AI model. Whether you’re a data scientist, developer, or just an AI enthusiast, this guide is user-friendly and straightforward!

Model Description

This model has been fine-tuned using 227,382 selected texts from a PTWiki dump, making it highly versatile for language processing tasks in Portuguese. The aim behind this model is purely educational, providing a Portuguese interface to the capabilities of GPT-Neo.

Getting Started: Installation and Dependencies

• Ensure you have Python installed.
• Install the Hugging Face Transformers library if you haven’t already:

pip install transformers

Loading the Model

To begin using the model, you’ll need to load both the tokenizer and the model itself using the following Python code:

from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("HeyLucasLeao/gpt-neo-small-portuguese")
model = AutoModelForCausalLM.from_pretrained("HeyLucasLeao/gpt-neo-small-portuguese")

Generating Text

Imagine how a chef prepares a special dish: they gather ingredients (the input text), follow a recipe (the code), and produce a delicious meal (the generated output). Similarly, in our code, we input a starting sentence and use the model to generate additional text based on that.

Here’s how to generate text step by step:

1. Prepare your input text, for example: eu amo o brasil.
2. Process the input text through the tokenizer:

generated = tokenizer("startoftext " + text, return_tensors="pt").input_ids.cuda()

3. Generate text using the model:

sample_outputs = model.generate(
    generated,
    do_sample=True,
    top_k=3,
    max_length=200,
    top_p=0.95,
    temperature=1.9,
    num_return_sequences=3
)

4. Finally, decode and print the generated sequences:

for i, sample_output in enumerate(sample_outputs):
    print(f"Generated text {i+1}: {tokenizer.decode(sample_output.tolist())}")

Troubleshooting

If you encounter issues while using the GPT-Neo Small Portuguese model, here are some troubleshooting steps:

• Ensure that your Python version is up-to-date.
• Check that all dependencies, especially the Transformers library, are installed properly.
• If CUDA runs into problems, consider switching to a CPU if you’re not using a GPU.

For more insights, updates, or to collaborate on AI development projects, stay connected with fxis.ai.

Concluding Thoughts

At fxis.ai, we believe that such advancements are crucial for the future of AI, as they enable more comprehensive and effective solutions. Our team is continually exploring new methodologies to push the envelope in artificial intelligence, ensuring that our clients benefit from the latest technological innovations.