| import gradio as gr | |
| from transformers import AutoTokenizer, AutoModelForCausalLM | |
| model_name = "your-username/my-wizardmath-finetuned" | |
| tokenizer = AutoTokenizer.from_pretrained(model_name) | |
| model = AutoModelForCausalLM.from_pretrained(model_name, device_map="auto") | |
| def generate_response(prompt): | |
| inputs = tokenizer(prompt, return_tensors="pt").to(model.device) | |
| outputs = model.generate(**inputs, max_new_tokens=256) | |
| return tokenizer.decode(outputs[0], skip_special_tokens=True) | |
| gr.Interface(fn=generate_response, | |
| inputs="text", | |
| outputs="text", | |
| title="WizardMath Fine-Tuned", | |
| description="Ask WizardMath anything!" | |
| ).launch() | |