| 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() |
|
|
