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import csv |
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from datetime import datetime |
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import os |
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from typing import Optional |
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import gradio as gr |
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from convert import convert |
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from huggingface_hub import HfApi, Repository |
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DATASET_REPO_URL = "https://huggingface.co/datasets/safetensors/conversions" |
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DATA_FILENAME = "data.csv" |
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DATA_FILE = os.path.join("data", DATA_FILENAME) |
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HF_TOKEN = os.environ.get("HF_TOKEN") |
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repo: Optional[Repository] = None |
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if False and HF_TOKEN: |
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repo = Repository(local_dir="data", clone_from=DATASET_REPO_URL, token=HF_TOKEN) |
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def run(model_id: str, is_private: bool, token: Optional[str] = None) -> str: |
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if model_id == "": |
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return """ |
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### Invalid input 🐞 |
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Please fill a token and model_id. |
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""" |
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try: |
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if is_private: |
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api = HfApi(token=token) |
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else: |
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api = HfApi(token=HF_TOKEN) |
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hf_is_private = api.model_info(repo_id=model_id).private |
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if is_private and not hf_is_private: |
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api = HfApi(token=HF_TOKEN) |
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print("is_private", is_private) |
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commit_info, errors = convert(api=api, model_id=model_id) |
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print("[commit_info]", commit_info) |
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string = f""" |
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### Success 🔥 |
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Yay! This model was successfully converted and a PR was open using your token, here: |
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[{commit_info.pr_url}]({commit_info.pr_url}) |
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""" |
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if errors: |
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string += "\nErrors during conversion:\n" |
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string += "\n".join(f"Error while converting {filename}: {e}, skipped conversion" for filename, e in errors) |
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return string |
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except Exception as e: |
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return f""" |
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### Error 😢😢😢 |
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{e} |
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""" |
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DESCRIPTION = """ |
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The steps are the following: |
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- Paste a read-access token from hf.co/settings/tokens. Read access is enough given that we will open a PR against the source repo. |
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- Input a model id from the Hub |
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- Click "Submit" |
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- That's it! You'll get feedback if it works or not, and if it worked, you'll get the URL of the opened PR 🔥 |
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⚠️ For now only `pytorch_model.bin` files are supported but we'll extend in the future. |
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""" |
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title="Convert any model to Safetensors and open a PR" |
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allow_flagging="never" |
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def token_text(visible=False): |
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return gr.Text(max_lines=1, label="your_hf_token", visible=visible) |
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with gr.Blocks(title=title) as demo: |
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description = gr.Markdown(f"""# {title}""") |
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description = gr.Markdown(DESCRIPTION) |
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with gr.Row() as r: |
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with gr.Column() as c: |
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model_id = gr.Text(max_lines=1, label="model_id") |
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is_private = gr.Checkbox(label="Private model") |
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token = token_text() |
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with gr.Row() as c: |
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clean = gr.ClearButton() |
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submit = gr.Button("Submit", variant="primary") |
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with gr.Column() as d: |
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output = gr.Markdown() |
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is_private.change(lambda s: token_text(s), inputs=is_private, outputs=token) |
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submit.click(run, inputs=[model_id, is_private, token], outputs=output, concurrency_limit=1) |
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demo.queue(max_size=10).launch(show_api=True) |
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