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fix maximum input token count exceeds limit of 4096 #244

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fix maximum input token count exceeds limit of 4096 #244

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4910f7a
typo: added space to 01_fine-tuning-titan-lite.ipynb
FireballDWF Apr 2, 2024
e7a5c00
fix Maximum input token count exceeds limit #224
FireballDWF Apr 3, 2024
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2 changes: 1 addition & 1 deletion 03_Model_customization/01_fine-tuning-titan-lite.ipynb
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Expand Up @@ -191,7 +191,7 @@
"\n",
"Amazon Titan text model customization hyperparameters: \n",
"- `epochs`: The number of iterations through the entire training dataset and can take up any integer values in the range of 1-10, with a default value of 5.\n",
"- `batchSize`: The number of samples processed before updating model parametersand can take up any integer values in the range of 1-64, with a default value of 1.\n",
"- `batchSize`: The number of samples processed before updating model parameters and can take up any integer values in the range of 1-64, with a default value of 1.\n",
"- `learningRate`:\tThe rate at which model parameters are updated after each batch\twhich can take up a float value betweek 0.0-1.0 with a default value set to\t1.00E-5.\n",
"- `learningRateWarmupSteps`: The number of iterations over which the learning rate is gradually increased to the specified rate and can take any integer value between 0-250 with a default value of 5.\n",
"\n",
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4 changes: 2 additions & 2 deletions 03_Model_customization/03_continued_pretraining_titan_text.ipynb
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Expand Up @@ -268,8 +268,8 @@
"# - in our testing Character split works better with this PDF data set\n",
"text_splitter = RecursiveCharacterTextSplitter(\n",
" # Set a really small chunk size, just to show.\n",
" chunk_size = 20000, # 4096 tokens * 6 chars per token = 24,576 \n",
" chunk_overlap = 2000, # overlap for continuity across chunks\n",
" chunk_size = 4000, # when set to 20000, got error "Maximum input token count 4919 exceeds limit of 4096". Orginal comment was 4096 tokens * 6 chars per token = 24,576 \n",
" chunk_overlap = 1000, # overlap for continuity across chunks\n",
")\n",
"\n",
"docs = text_splitter.split_documents(document)"
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