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Minor fixes

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Andras Schmelczer 2022-07-29 11:05:37 +02:00
parent 4d55499548
commit 2b7188b1b8
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2 changed files with 3 additions and 4 deletions
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5
docs/examples/scibert/deploy.ipynb
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@ -182,9 +182,8 @@
" positive_likelihood = torch.nn.Softmax(dim=1)(result.logits)[0][1]\n", " positive_likelihood = torch.nn.Softmax(dim=1)(result.logits)[0][1]\n",
" tokens = tensors[\"input_ids\"][0]\n", " tokens = tensors[\"input_ids\"][0]\n",
"\n", "\n",
" attentions = np.sum(result.attentions[-1].numpy()[0], axis=0)[0][\n", " attentions = np.sum(result.attentions[-1].numpy()[0], axis=0)[0][1:-1]\n",
" 1:-1\n", " # Tuple of `torch.FloatTensor` (one for each layer) of shape\n",
" ] # Tuple of `torch.FloatTensor` (one for each layer) of shape\n",
" # `(batch_size, num_heads, sequence_length, sequence_length)`.\n", " # `(batch_size, num_heads, sequence_length, sequence_length)`.\n",
"\n", "\n",
" explanation = []\n", " explanation = []\n",

2
docs/examples/scibert/train.ipynb
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@ -246,7 +246,7 @@
" Dataset.from_dict({\"text\": X, \"label\": y})\n", " Dataset.from_dict({\"text\": X, \"label\": y})\n",
" .map(lambda v: tokenizer(v[\"text\"], truncation=True), batched=True)\n", " .map(lambda v: tokenizer(v[\"text\"], truncation=True), batched=True)\n",
" .remove_columns(\"text\")\n", " .remove_columns(\"text\")\n",
" .train_test_split(test_size=0.2, shuffle=True)\n", " .train_test_split(test_size=0.2, shuffle=True) # test is actually validation\n",
")\n", ")\n",
"\n", "\n",
"f1_score = load_metric(\"f1\")\n", "f1_score = load_metric(\"f1\")\n",