| import csv |
| import os |
| from datetime import datetime |
| from typing import Optional, Union |
| import gradio as gr |
| from huggingface_hub import HfApi, Repository |
| from export import convert |
|
|
|
|
| DATASET_REPO_URL = "https://huggingface.co/datasets/optimum/exporters" |
| DATA_FILENAME = "data.csv" |
| DATA_FILE = os.path.join("openvino", DATA_FILENAME) |
| HF_TOKEN = os.environ.get("HF_WRITE_TOKEN") |
| DATA_DIR = "exporters_data" |
|
|
| repo = None |
| if HF_TOKEN: |
| repo = Repository(local_dir=DATA_DIR, clone_from=DATASET_REPO_URL, token=HF_TOKEN) |
|
|
|
|
| def export(token: str, model_id: str, task: str) -> str: |
| if token == "" or model_id == "": |
| return """ |
| ### Invalid input 🐞 |
| Please fill a token and model name. |
| """ |
| try: |
| api = HfApi(token=token) |
|
|
| error, commit_info = convert(api=api, model_id=model_id, task=task, force=False) |
| if error != "0": |
| return error |
|
|
| print("[commit_info]", commit_info) |
|
|
| |
| if repo is not None: |
| repo.git_pull(rebase=True) |
| with open(os.path.join(DATA_DIR, DATA_FILE), "a") as csvfile: |
| writer = csv.DictWriter(csvfile, fieldnames=["model_id", "pr_url", "time"]) |
| writer.writerow( |
| { |
| "model_id": model_id, |
| "pr_url": commit_info.pr_url, |
| "time": str(datetime.now()), |
| } |
| ) |
| commit_url = repo.push_to_hub() |
| print("[dataset]", commit_url) |
|
|
| return f"#### Success 🔥 Yay! This model was successfully exported and a PR was open using your token, here: [{commit_info.pr_url}]({commit_info.pr_url})" |
| except Exception as e: |
| return f"#### Error: {e}" |
|
|
|
|
| TTILE_IMAGE = """ |
| <div |
| style=" |
| display: block; |
| margin-left: auto; |
| margin-right: auto; |
| width: 50%; |
| " |
| > |
| <img src="https://huggingface.co/spaces/echarlaix/openvino-export/resolve/main/header.png"/> |
| </div> |
| """ |
|
|
| TITLE = """ |
| <div |
| style=" |
| display: inline-flex; |
| align-items: center; |
| text-align: center; |
| max-width: 1400px; |
| gap: 0.8rem; |
| font-size: 2.2rem; |
| " |
| > |
| <h1 style="font-weight: 900; margin-bottom: 10px; margin-top: 10px;"> |
| Export your Transformers and Diffusers model to OpenVINO with 🤗 Optimum Intel (experimental) |
| </h1> |
| </div> |
| """ |
|
|
| DESCRIPTION = """ |
| This Space allows you to automatically export to the OpenVINO format various 🤗 Transformers and Diffusers PyTorch models hosted on the Hugging Face Hub. |
| |
| Once exported, you will be able to load the resulting model using the [🤗 Optimum Intel](https://huggingface.co/docs/optimum/intel/inference). |
| |
| To export your model, the steps are as following: |
| - Paste a read-access token from [https://huggingface.co/settings/tokens](https://huggingface.co/settings/tokens). Read access is enough given that we will open a PR against the source repo. |
| - Input a model id from the Hub (for example: [distilbert-base-uncased-finetuned-sst-2-english](https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english)) |
| - Click "Export" |
| - 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 🔥 |
| """ |
|
|
| with gr.Blocks() as demo: |
| gr.HTML(TTILE_IMAGE) |
| gr.HTML(TITLE) |
|
|
| with gr.Row(): |
| with gr.Column(scale=50): |
| gr.Markdown(DESCRIPTION) |
|
|
| with gr.Column(scale=50): |
| input_token = gr.Textbox( |
| max_lines=1, |
| label="Hugging Face token", |
| ) |
| input_model = gr.Textbox( |
| max_lines=1, |
| label="Model name", |
| placeholder="distilbert-base-uncased-finetuned-sst-2-english", |
| ) |
| input_task = gr.Textbox( |
| value="auto", |
| max_lines=1, |
| label='Task (can be left to "auto", will be automatically inferred)', |
| ) |
|
|
| btn = gr.Button("Export") |
| output = gr.Markdown(label="Output") |
|
|
| btn.click( |
| fn=export, |
| inputs=[input_token, input_model, input_task], |
| outputs=output, |
| ) |
|
|
|
|
| demo.launch() |
|
|
