| import gradio as gr | |
| from transformers import pipeline | |
| def embed_html(html_frame): | |
| return gr.outputs.HTML(html_frame) | |
| def hugging_face_fn(inputs): | |
| return {"output": embed_html(inputs)} | |
| iface = gr.Interface( | |
| fn=hugging_face_fn, | |
| inputs=gr.inputs.Textbox(label="Enter HTML frame here"), | |
| outputs="html", | |
| title="HTML Frame Embedder", | |
| description="Input an HTML frame and see it embedded below." | |
| ) | |
| model = pipeline("text-generation", model="gpt2") | |
| model.add_pipe(iface) | |
| model("Hello world! This is an HTML frame <iframe src='https://www.example.com'></iframe>") | |