Hugging Face Transformers library

from transformers import AutoModelForCausalLM, AutoTokenizer, TrainingArguments, Trainer

# Load pre-trained model and tokenizer
model = AutoModelForCausalLM.from_pretrained("gpt2")
tokenizer = AutoTokenizer.from_pretrained("gpt2")

# Prepare your domain-specific dataset
train_dataset = ...  # Your custom dataset

# Define training arguments
training_args = TrainingArguments(
    output_dir="./results",
    num_train_epochs=3,
    per_device_train_batch_size=8,
    save_steps=10_000,
    save_total_limit=2,
)

# Initialize Trainer
trainer = Trainer(
    model=model,
    args=training_args,
    train_dataset=train_dataset,
)

# Fine-tune the model
trainer.train()

# Save the fine-tuned model
model.save_pretrained("./fine_tuned_model")
tokenizer.save_pretrained("./fine_tuned_model")