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| from gradio_client import Client, handle_file | |
| from huggingface_hub import HfApi | |
| import time | |
| import gradio as gr | |
| api = HfApi() | |
| repo_ids = ["HuggingFaceH4/idefics2-8b-playground"] | |
| for repo_id in repo_ids: | |
| if api.space_info(repo_id).runtime.stage not in ["RUNNING", "APP_STARTING", "RUNNING_APP_STARTING"]: | |
| api.restart_space(repo_id="HuggingFaceH4/idefics2-8b-playground") | |
| for repo_id in repo_ids: | |
| while api.space_info(repo_id).runtime.stage != "RUNNING": | |
| time.sleep(1) | |
| client_idefics2 = Client("HuggingFaceH4/idefics2-8b-playground") | |
| def respond(multimodal_input): | |
| x = {"text": multimodal_input["text"], "files": [handle_file(file) for file in multimodal_input["files"]]} | |
| text_1 = client_idefics2.predict(x, api_name="/predict") | |
| return text_1 | |
| gr.Interface( | |
| respond, | |
| title="Compare IDEFICS2-8B Against DPO", | |
| description="Chatchat made by Peterpeter8585", | |
| inputs=[gr.MultimodalTextbox(file_types=["image"], show_label=False)], | |
| outputs=[gr.Textbox(label="idefics2-8b")], | |
| examples=[{"text": "What is the type of flower in the image and what insect is on it?", "files": ["./bee.jpg"]}, | |
| {"text": "Describe the image", "files": ["./howl.jpg"]}], | |
| ).launch(show_error=True) | |