davanstrien HF staff commited on
Commit
a47ca85
1 Parent(s): 5e69434
Files changed (1) hide show
  1. app.py +1 -1
app.py CHANGED
@@ -164,7 +164,7 @@ with gr.Blocks() as demo:
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  You can use this to test out [image classification models](https://huggingface.co/models?pipeline_tag=image-classification) on the Hugging Face Hub:
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  - To use this tab you will need to have a Hugging Face account and a valid token.
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  - You can get a token from your [Hugging Face account page](https://huggingface.co/settings/token).
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- - Input this token into the token box and then input a valid image classification model id from the Hub. For example `microsoft/resnet-50`. You can use the [Hub]((https://huggingface.co/models?pipeline_tag=image-classification) to find suitable models.
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  This tab uses Hugging Face's [Inference API](https://huggingface.co/docs/api-inference/index) to make predictions. It will randomly select 10 images from your dataset and make predictions on them using your chosen model.
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  **Please note** the predictions will take some time since the model needs to be loaded for inference first. If you make a second batch of prediction using the same model the predictions should be quicker."""
 
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  You can use this to test out [image classification models](https://huggingface.co/models?pipeline_tag=image-classification) on the Hugging Face Hub:
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  - To use this tab you will need to have a Hugging Face account and a valid token.
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  - You can get a token from your [Hugging Face account page](https://huggingface.co/settings/token).
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+ - Input this token into the token box and then input a valid image classification model id from the Hub. For example `microsoft/resnet-50`. You can use the [Hub](https://huggingface.co/models?pipeline_tag=image-classification) to find suitable models.
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  This tab uses Hugging Face's [Inference API](https://huggingface.co/docs/api-inference/index) to make predictions. It will randomly select 10 images from your dataset and make predictions on them using your chosen model.
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  **Please note** the predictions will take some time since the model needs to be loaded for inference first. If you make a second batch of prediction using the same model the predictions should be quicker."""