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update notebook kwarg to use verbose
Signed-off-by: GiulioZizzo <[email protected]>
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notebooks/huggingface_notebook.ipynb

Lines changed: 4 additions & 4 deletions
Original file line numberDiff line numberDiff line change
@@ -134,7 +134,7 @@
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" nb_classes=10,\n",
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" clip_values=(0, 1),\n",
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" processor=upsampler)\n",
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" hf_model.fit(x_train, y_train, nb_epochs=2, display_progress_bar=True)\n",
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" hf_model.fit(x_train, y_train, nb_epochs=2, verbose=True)\n",
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" return hf_model"
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]
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},
@@ -701,7 +701,7 @@
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" clip_values=(0, 1),\n",
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" processor=upsampler)\n",
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" (x_train, y_train), (x_test, y_test) = get_cifar_data(train_on_subset)\n",
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" hf_model.fit(x_train, y_train, nb_epochs=2, display_progress_bar=True)\n",
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" hf_model.fit(x_train, y_train, nb_epochs=2, verbose=True)\n",
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"\n",
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" return hf_model"
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]
@@ -1010,7 +1010,7 @@
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" processor=None) # No processor is needed as the data is of the correct size for the model.\n",
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" \n",
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" (x_train, y_train), (x_test, y_test) = get_cifar_data()\n",
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" simple_hf_classifier.fit(x_train, y_train, nb_epochs=20, display_progress_bar=True)\n",
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" simple_hf_classifier.fit(x_train, y_train, nb_epochs=20, verbose=True)\n",
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"\n",
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" num_samples = 100\n",
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" outputs = simple_hf_classifier.predict(x_test[:num_samples])\n",
@@ -1363,7 +1363,7 @@
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.10.12"
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"version": "3.8.10"
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}
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},
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"nbformat": 4,

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