Category : bert-language-model

[First I would like to thank the community of SO; for whose support I could actually finish making an end to end data science project (including deployment.)] Over to my question. I wanted to create an app that will predict success or failure depending upon textual input data. In order to construct the model; instead ..

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I am working on a project where I have to extract specific information from PDFs file like Document ID, Amount, Processing Fees, Description, Dates, Organization, Authority name, Department and many such things. Here description can be of few lines but other information will be of few characters. Challenge: No two PDFs are of same format ..

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At the moment my model gives 3 output tensors. I want two of them to be more cooperative. I want to use the combination of self.dropout1(hs) and self.dropout2(cls_hs) to pass through the self.entity_out Linear Layer. The issue is mentioned 2 tensors are in different shapes. Current Code class NLUModel(nn.Module): def __init__(self, num_entity, num_intent, num_scenarios): super(NLUModel, ..

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I am using huggingface transformers models for quite a few tasks, it works good but the only problem is the response time. It takes around 6-7 seconds to generate result while some times it even takes around 15-20 seconds. I tried on google collab using GPU, the performance in GPU is too fast within just ..

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