| import gradio as gr | |
| from transformers import AutoTokenizer, AutoModelForCausalLM | |
| import os | |
| model_id = "i99om/phi-2" | |
| token = os.environ.get("HF_TOKEN") | |
| tokenizer = AutoTokenizer.from_pretrained(model_id, use_auth_token=token) | |
| model = AutoModelForCausalLM.from_pretrained(model_id, use_auth_token=token) | |
| def generate_text(prompt): | |
| inputs = tokenizer(prompt, return_tensors="pt") | |
| outputs = model.generate(**inputs, max_new_tokens=150) | |
| return tokenizer.decode(outputs[0], skip_special_tokens=True) | |
| with gr.Blocks(api=True) as demo: | |
| textbox = gr.Textbox(label="ุฃุฏุฎู ุงููุต") | |
| output = gr.Textbox(label="ุงููุงุชุฌ") | |
| btn = gr.Button("ุชูููุฏ") | |
| btn.click(generate_text, inputs=textbox, outputs=output) | |
| demo.launch() | |