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import marimo |
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__generated_with = "0.11.5" |
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app = marimo.App(width="medium") |
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@app.cell |
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def _(): |
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import marimo as mo |
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return (mo,) |
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@app.cell(hide_code=True) |
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def _(mo): |
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default_model = mo.query_params().get("model") or "" |
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model_repo = mo.ui.text( |
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label="Model repo", |
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full_width=True, |
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value=default_model, |
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placeholder="e.g. gpt2, bert-base-uncased", |
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).form(bordered=False) |
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model_repo |
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return default_model, model_repo |
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@app.cell(hide_code=True) |
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def _(mo): |
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mo.md( |
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r""" |
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Interactively try out AI models hosted on HuggingFace! |
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Some popular models to try: |
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- **Feature Extraction**: `julien-c/distilbert-feature-extraction` |
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- **Text to Speech**: `julien-c/ljspeech_tts_train_tacotron2_raw_phn_tacotron_g2p_en_no_space_train` |
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- **Text to Image**: `runwayml/stable-diffusion-v1-5` |
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""" |
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) |
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return |
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@app.cell(hide_code=True) |
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def _(mo): |
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mo.accordion( |
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{ |
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"View more": mo.md(""" |
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_Audio Models_ |
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- **Audio Classification**: `ehcalabres/wav2vec2-lg-xlsr-en-speech-emotion-recognition` |
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- **Audio to Audio**: `facebook/xm_transformer_sm_all-en` |
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- **Speech Recognition**: `facebook/wav2vec2-base-960h` |
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_Image Models_ |
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- **Image Classification**: `google/vit-base-patch16-224` |
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- **Image to Text**: `Salesforce/blip-image-captioning-base` |
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- **Object Detection**: `microsoft/table-transformer-detection` |
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_Text Models_ |
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- **Fill Mask**: `distilbert/distilbert-base-uncased` |
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- **Zero-shot Classification**: `facebook/bart-large-mnli` |
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- **Sentence Similarity**: `sentence-transformers/all-MiniLM-L6-v2` |
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""") |
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} |
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) |
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return |
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@app.cell(hide_code=True) |
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def _(mo): |
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token = mo.ui.text( |
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label="HuggingFace token (optional)", |
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kind="password", |
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).form(bordered=False) |
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mo.accordion({"Enter your HuggingFace token (optional)": token}) |
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return (token,) |
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@app.cell(hide_code=True) |
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def _(mo, model_repo, molabs, token): |
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if not model_repo.value: |
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mo.stop("Please enter a model name") |
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model_path = "models/" + model_repo.value.replace("models/", "") |
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model = molabs.huggingface.load( |
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model_path, hf_token=token.value if token.value else None |
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) |
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return model, model_path |
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@app.cell(hide_code=True) |
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def _(mo, model): |
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mo.stop(not model) |
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mo.md( |
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f""" |
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### Example inputs |
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Try these sample inputs with the model: |
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{mo.as_html(model.examples)} |
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""" |
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) |
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return |
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@app.cell(hide_code=True) |
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def _(mo, model): |
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inputs = model.inputs |
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mo.vstack( |
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[ |
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mo.md("### Model Inputs"), |
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mo.md("_Submit inputs below to run inference_ 👇"), |
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inputs, |
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], |
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) |
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return (inputs,) |
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@app.cell(hide_code=True) |
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def _(inputs, mo, model): |
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if inputs.value is None: |
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mo.stop("Please provide input values") |
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with mo.status.spinner("Running inference..."): |
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output = model.inference_function(inputs.value) |
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mo.output.replace(mo.vstack([mo.md("### Results"), output])) |
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return (output,) |
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@app.cell |
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def _(): |
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import sys |
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import marimo_labs as molabs |
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return molabs, sys |
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if __name__ == "__main__": |
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app.run() |
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