from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("LucasFMartins/gemma-3-1b-pt-fine-tuned-test")
model = AutoModelForCausalLM.from_pretrained("LucasFMartins/gemma-3-1b-pt-fine-tuned-test")

# Generate text
inputs = tokenizer("Your prompt here", return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=100)
response = tokenizer.decode(outputs[0], skip_special_tokens=True)
print(response)

Training Details

Base Model: google/gemma-3-1b-pt
Fine-tuning Method: LoRA (Low-Rank Adaptation)
Training Platform: Gemma Garage
Fine-tuned on: 2025-07-12

This model was fine-tuned using the Gemma Garage platform with the following configuration:

Request ID: ffc7df82-b582-43f2-8ebe-0d3684182c05
Training completed on: 2025-07-12 01:57:32 UTC

For more information about Gemma Garage, visit our GitHub repository.