from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("charitas/gemma-3-1b-it-fine-tuned")
model = AutoModelForCausalLM.from_pretrained("charitas/gemma-3-1b-it-fine-tuned")

# 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-it
Fine-tuning Method: LoRA (Low-Rank Adaptation)
Training Platform: Gemma Garage
Fine-tuned on: 2025-11-03

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

Request ID: 8811309a-609b-4bd6-9513-d761e36a9381
Training completed on: 2025-11-03 10:24:23 UTC

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