| from transformers import AutoModelForCausalLM, AutoTokenizer | |
| import torch | |
| import gradio as gr | |
| model = AutoModelForCausalLM.from_pretrained("atsnetwork/my-custom-tinyllama-chatbot") | |
| tokenizer = AutoTokenizer.from_pretrained("atsnetwork/my-custom-tinyllama-chatbot") | |
| def generate_response(prompt): | |
| inputs = tokenizer(prompt, return_tensors="pt") | |
| outputs = model.generate(**inputs, max_new_tokens=100) | |
| return tokenizer.decode(outputs[0], skip_special_tokens=True) | |
| iface = gr.Interface(fn=generate_response, inputs="text", outputs="text") | |
| iface.launch() |