| # Load model directly and generate text from a test string | |
| from transformers import AutoTokenizer, AutoModelForCausalLM | |
| tokenizer = AutoTokenizer.from_pretrained("Nbardy/mini-mistral") | |
| model = AutoModelForCausalLM.from_pretrained("Nbardy/mini-mistral") | |
| # Prepare the test string for input | |
| input_text = "This is a test string" | |
| input_ids = tokenizer.encode(input_text, return_tensors="pt") | |
| # Generate text using the model | |
| output = model.generate(input_ids) | |
| # Decode and print the generated text | |
| generated_text = tokenizer.decode(output[0], skip_special_tokens=True) | |
| print(generated_text) | |