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fix notebook formatting
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@bebechien
bebechien committed Jun 27, 2024
1 parent 7142085 commit 01ddfd4
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125 changes: 57 additions & 68 deletions Gemma/Keras_Gemma_2_Quickstart.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -113,17 +113,12 @@
"cell_type": "code",
"execution_count": 3,
"metadata": {
"id": "ww83zI9ToPso",
"outputId": "2ffbb6b0-e3b2-4f8f-b614-0c5e1dfa4adf",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 717
}
"id": "ww83zI9ToPso"
},
"outputs": [
{
"output_type": "stream",
"name": "stderr",
"output_type": "stream",
"text": [
"Downloading from https://www.kaggle.com/api/v1/models/keras/gemma2/keras/gemma2_9b_en/1/download/model.safetensors...\n",
"Downloading from https://www.kaggle.com/api/v1/models/keras/gemma2/keras/gemma2_9b_en/1/download/model.safetensors.index.json...\n",
Expand All @@ -146,70 +141,54 @@
]
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"\u001b[1mPreprocessor: \"gemma_causal_lm_preprocessor\"\u001b[0m\n"
],
"text/html": [
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">Preprocessor: \"gemma_causal_lm_preprocessor\"</span>\n",
"</pre>\n"
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"text/plain": [
"\u001b[1mPreprocessor: \"gemma_causal_lm_preprocessor\"\u001b[0m\n"
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"┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓\n",
"┃\u001b[1m \u001b[0m\u001b[1mTokenizer (type) \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m Vocab #\u001b[0m\u001b[1m \u001b[0m┃\n",
"┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┩\n",
"│ gemma_tokenizer (\u001b[38;5;33mGemmaTokenizer\u001b[0m) │ \u001b[38;5;34m256,000\u001b[0m │\n",
"└────────────────────────────────────────────────────┴─────────────────────────────────────────────────────┘\n"
],
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"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓\n",
"┃<span style=\"font-weight: bold\"> Tokenizer (type) </span>┃<span style=\"font-weight: bold\"> Vocab # </span>┃\n",
"┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┩\n",
"│ gemma_tokenizer (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">GemmaTokenizer</span>) │ <span style=\"color: #00af00; text-decoration-color: #00af00\">256,000</span> │\n",
"└────────────────────────────────────────────────────┴─────────────────────────────────────────────────────┘\n",
"</pre>\n"
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"┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓\n",
"┃\u001b[1m \u001b[0m\u001b[1mTokenizer (type) \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m Vocab #\u001b[0m\u001b[1m \u001b[0m┃\n",
"┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┩\n",
"│ gemma_tokenizer (\u001b[38;5;33mGemmaTokenizer\u001b[0m) │ \u001b[38;5;34m256,000\u001b[0m │\n",
"└────────────────────────────────────────────────────┴─────────────────────────────────────────────────────┘\n"
]
},
"metadata": {}
"metadata": {},
"output_type": "display_data"
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"\u001b[1mModel: \"gemma_causal_lm\"\u001b[0m\n"
],
"text/html": [
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">Model: \"gemma_causal_lm\"</span>\n",
"</pre>\n"
],
"text/plain": [
"\u001b[1mModel: \"gemma_causal_lm\"\u001b[0m\n"
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"metadata": {},
"output_type": "display_data"
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{
"output_type": "display_data",
"data": {
"text/plain": [
"┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓\n",
"┃\u001b[1m \u001b[0m\u001b[1mLayer (type) \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mOutput Shape \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m Param #\u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mConnected to \u001b[0m\u001b[1m \u001b[0m┃\n",
"┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━┩\n",
"│ padding_mask (\u001b[38;5;33mInputLayer\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;45mNone\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │ - │\n",
"├───────────────────────────────┼───────────────────────────┼─────────────────┼────────────────────────────┤\n",
"│ token_ids (\u001b[38;5;33mInputLayer\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;45mNone\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │ - │\n",
"├───────────────────────────────┼───────────────────────────┼─────────────────┼────────────────────────────┤\n",
"│ gemma_backbone │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m3584\u001b[0m) │ \u001b[38;5;34m9,241,705,984\u001b[0m │ padding_mask[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m], │\n",
"│ (\u001b[38;5;33mGemmaBackbone\u001b[0m) │ │ │ token_ids[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m] │\n",
"├───────────────────────────────┼───────────────────────────┼─────────────────┼────────────────────────────┤\n",
"│ token_embedding │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m256000\u001b[0m) │ \u001b[38;5;34m917,504,000\u001b[0m │ gemma_backbone[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m] │\n",
"│ (\u001b[38;5;33mReversibleEmbedding\u001b[0m) │ │ │ │\n",
"└───────────────────────────────┴───────────────────────────┴─────────────────┴────────────────────────────┘\n"
],
"text/html": [
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓\n",
"┃<span style=\"font-weight: bold\"> Layer (type) </span>┃<span style=\"font-weight: bold\"> Output Shape </span>┃<span style=\"font-weight: bold\"> Param # </span>┃<span style=\"font-weight: bold\"> Connected to </span>┃\n",
Expand All @@ -225,48 +204,64 @@
"│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">ReversibleEmbedding</span>) │ │ │ │\n",
"└───────────────────────────────┴───────────────────────────┴─────────────────┴────────────────────────────┘\n",
"</pre>\n"
],
"text/plain": [
"┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓\n",
"┃\u001b[1m \u001b[0m\u001b[1mLayer (type) \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mOutput Shape \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m Param #\u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mConnected to \u001b[0m\u001b[1m \u001b[0m┃\n",
"┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━┩\n",
"│ padding_mask (\u001b[38;5;33mInputLayer\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;45mNone\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │ - │\n",
"├───────────────────────────────┼───────────────────────────┼─────────────────┼────────────────────────────┤\n",
"│ token_ids (\u001b[38;5;33mInputLayer\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;45mNone\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │ - │\n",
"├───────────────────────────────┼───────────────────────────┼─────────────────┼────────────────────────────┤\n",
"│ gemma_backbone │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m3584\u001b[0m) │ \u001b[38;5;34m9,241,705,984\u001b[0m │ padding_mask[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m], │\n",
"│ (\u001b[38;5;33mGemmaBackbone\u001b[0m) │ │ │ token_ids[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m] │\n",
"├───────────────────────────────┼───────────────────────────┼─────────────────┼────────────────────────────┤\n",
"│ token_embedding │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m256000\u001b[0m) │ \u001b[38;5;34m917,504,000\u001b[0m │ gemma_backbone[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m] │\n",
"│ (\u001b[38;5;33mReversibleEmbedding\u001b[0m) │ │ │ │\n",
"└───────────────────────────────┴───────────────────────────┴─────────────────┴────────────────────────────┘\n"
]
},
"metadata": {}
"metadata": {},
"output_type": "display_data"
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"\u001b[1m Total params: \u001b[0m\u001b[38;5;34m9,241,705,984\u001b[0m (17.21 GB)\n"
],
"text/html": [
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Total params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">9,241,705,984</span> (17.21 GB)\n",
"</pre>\n"
],
"text/plain": [
"\u001b[1m Total params: \u001b[0m\u001b[38;5;34m9,241,705,984\u001b[0m (17.21 GB)\n"
]
},
"metadata": {}
"metadata": {},
"output_type": "display_data"
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"\u001b[1m Trainable params: \u001b[0m\u001b[38;5;34m9,241,705,984\u001b[0m (17.21 GB)\n"
],
"text/html": [
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">9,241,705,984</span> (17.21 GB)\n",
"</pre>\n"
],
"text/plain": [
"\u001b[1m Trainable params: \u001b[0m\u001b[38;5;34m9,241,705,984\u001b[0m (17.21 GB)\n"
]
},
"metadata": {}
"metadata": {},
"output_type": "display_data"
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"\u001b[1m Non-trainable params: \u001b[0m\u001b[38;5;34m0\u001b[0m (0.00 B)\n"
],
"text/html": [
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Non-trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> (0.00 B)\n",
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"text/plain": [
"\u001b[1m Non-trainable params: \u001b[0m\u001b[38;5;34m0\u001b[0m (0.00 B)\n"
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},
"metadata": {}
"metadata": {},
"output_type": "display_data"
}
],
"source": [
Expand All @@ -285,16 +280,12 @@
"cell_type": "code",
"execution_count": 9,
"metadata": {
"id": "aae5GHrdpj2_",
"outputId": "718a5755-f7d8-42ad-f2af-a2a2b57ae710",
"colab": {
"base_uri": "https://localhost:8080/"
}
"id": "aae5GHrdpj2_"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"output_type": "stream",
"text": [
"It was a dark and stormy night.\n",
"\n",
Expand Down Expand Up @@ -344,9 +335,7 @@
"accelerator": "GPU",
"colab": {
"name": "Keras_Gemma_2_Quickstart.ipynb",
"toc_visible": true,
"provenance": [],
"gpuType": "A100"
"toc_visible": true
},
"kernelspec": {
"display_name": "Python 3",
Expand All @@ -355,4 +344,4 @@
},
"nbformat": 4,
"nbformat_minor": 0
}
}
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