| from transformers import AutoModelForCausalLM, AutoTokenizer | |
| # Set the path to your model and tokenizer | |
| model_directory = "/workspace/mergekit/output-model-directory" | |
| tokenizer_directory = "/workspace/mergekit/output-model-directory" | |
| # Load the tokenizer | |
| tokenizer = AutoTokenizer.from_pretrained(tokenizer_directory, ignore_mismatched_sizes=True) | |
| # Load the model | |
| model = AutoModelForCausalLM.from_pretrained(model_directory, ignore_mismatched_sizes=True) | |
| input_text = "Example input text here" | |
| inputs = tokenizer(input_text, return_tensors="pt") | |
| # Generate predictions | |
| outputs = model.generate(inputs['input_ids'], max_length=50) | |
| # Decode generated ids to text | |
| generated_text = tokenizer.decode(outputs[0], skip_special_tokens=True) | |
| print(generated_text) | |