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] | |
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"a557bc16af0c4baf8d71442864af6e43", | |
"57d898dc8a464b25a2921aa9089c1121", | |
"7a24fa64db0443179c5459117088aedb", | |
"6ef7842cf4ce47f1b4e5193ba589983a", | |
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}, | |
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{ | |
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"text": [ | |
"/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_token.py:88: UserWarning: \n", | |
"The secret `HF_TOKEN` does not exist in your Colab secrets.\n", | |
"To authenticate with the Hugging Face Hub, create a token in your settings tab (https://huggingface.co/settings/tokens), set it as secret in your Google Colab and restart your session.\n", | |
"You will be able to reuse this secret in all of your notebooks.\n", | |
"Please note that authentication is recommended but still optional to access public models or datasets.\n", | |
" warnings.warn(\n" | |
] | |
}, | |
{ | |
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"data": { | |
"text/plain": [ | |
"config.json: 0%| | 0.00/570 [00:00<?, ?B/s]" | |
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} | |
}, | |
"metadata": {} | |
}, | |
{ | |
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"data": { | |
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"model.safetensors: 0%| | 0.00/440M [00:00<?, ?B/s]" | |
], | |
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} | |
}, | |
"metadata": {} | |
}, | |
{ | |
"output_type": "stream", | |
"name": "stderr", | |
"text": [ | |
"All PyTorch model weights were used when initializing TFBertForSequenceClassification.\n", | |
"\n", | |
"Some weights or buffers of the TF 2.0 model TFBertForSequenceClassification were not initialized from the PyTorch model and are newly initialized: ['classifier.weight', 'classifier.bias']\n", | |
"You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n" | |
] | |
} | |
], | |
"source": [ | |
"from transformers import TFBertForSequenceClassification\n", | |
"model = TFBertForSequenceClassification.from_pretrained('bert-base-uncased')" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"source": [ | |
"import tensorflow as tf" | |
], | |
"metadata": { | |
"id": "etl2kX0nKU3z" | |
}, | |
"execution_count": 2, | |
"outputs": [] | |
}, | |
{ | |
"cell_type": "code", | |
"source": [ | |
"tf.__version__" | |
], | |
"metadata": { | |
"colab": { | |
"base_uri": "https://localhost:8080/", | |
"height": 37 | |
}, | |
"id": "oVhfUstZKaU4", | |
"outputId": "563d714b-dbc3-45bb-d305-11e823e02a0f" | |
}, | |
"execution_count": 3, | |
"outputs": [ | |
{ | |
"output_type": "execute_result", | |
"data": { | |
"text/plain": [ | |
"'2.15.0'" | |
], | |
"application/vnd.google.colaboratory.intrinsic+json": { | |
"type": "string" | |
} | |
}, | |
"metadata": {}, | |
"execution_count": 3 | |
} | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"source": [ | |
"import keras" | |
], | |
"metadata": { | |
"id": "OcSvcatSKzxU" | |
}, | |
"execution_count": 4, | |
"outputs": [] | |
}, | |
{ | |
"cell_type": "code", | |
"source": [ | |
"keras.__version__" | |
], | |
"metadata": { | |
"colab": { | |
"base_uri": "https://localhost:8080/", | |
"height": 37 | |
}, | |
"id": "7wDgj10XK3WV", | |
"outputId": "1b5d6dc1-d7c9-41d7-9139-b4d702b49879" | |
}, | |
"execution_count": 5, | |
"outputs": [ | |
{ | |
"output_type": "execute_result", | |
"data": { | |
"text/plain": [ | |
"'2.15.0'" | |
], | |
"application/vnd.google.colaboratory.intrinsic+json": { | |
"type": "string" | |
} | |
}, | |
"metadata": {}, | |
"execution_count": 5 | |
} | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"source": [ | |
"import os\n", | |
"os.environ[\"TF_USE_LEGACY_KERAS\"] =\"1\"" | |
], | |
"metadata": { | |
"id": "EaPWJA_VLaPK" | |
}, | |
"execution_count": 6, | |
"outputs": [] | |
}, | |
{ | |
"cell_type": "code", | |
"source": [ | |
"optimizer = tf.keras.optimizers.Adam(learning_rate=2e-5)\n", | |
"loss = tf.keras.losses.SparseCategoricalCrossentropy(from_logits=True)\n", | |
"metric = tf.keras.metrics.SparseCategoricalAccuracy('accuracy')\n", | |
"model.compile(optimizer=optimizer, loss=loss, metrics=[metric])" | |
], | |
"metadata": { | |
"id": "wZTysYXuK42N" | |
}, | |
"execution_count": 7, | |
"outputs": [] | |
} | |
] | |
} |
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