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Questions - deep-learning

Using the encoder part only from T5 model

I want to build a classification model that needs only the encoder part of language models. I have tried Bert, Roberta, xlnet, and so far I have been successful. I now want to test the encoder part on...
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ls_grep

deep-learning

pytorch

huggingface-transformers

transformer-model

encoder-decoder

Votes: 0

Answers: 1

Latest Answer

Load T5 encoder checkpoint only: from transformers import T5EncoderModel T5EncoderModel._keys_to_ignore_on_load_unexpected = ["decoder.*"] auto_model = T5EncoderModel.from_pretrained("t...
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Dương Xuân Hiếu

Does Batch Size matter if I only care about deploying and not training?

Gonna ask a newbie question... If I finished training my model, or I am using trained model like YOLO. And I want to put the model on a robot that has a 6GB VRAM. In this case, do I need to concern ab...
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user3084686

deep-learning

gpu

Votes: 0

Answers: 1

Latest Answer

Generally speaking, batch size can be adjusted at any time without creating a problem. Each element of a batch is independent, but they are fed through the network together for efficiency reasons. Not...
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user253751

Changing RGB channel intensities using Keras ImageDataGenerator

I have been trying to augment my around 360 images while training a model. This is how the code looks like img_data_gen_args = dict(rotation_range=90, width_shift_range=0.3, ...
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Dan Py

deep-learning

conv-neural-network

rgb

tf.keras

image-augmentation

Votes: 0

Answers: 1

Latest Answer

You can add a preprocessing_function to the img_data_gen_args dictionary like you do for the mask_data_gen_args dictionary. Inside the function, you can change the RGB color intensities as you like. A...
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Ali Haider

Joining the output of 2 Keras layers

I am trying to implement a joint model using Keras, and this is the architecture of the model. However, I have difficulty in the concatenation of inputs from the subnetwork and the main network. The ...
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ray

python

tensorflow

machine-learning

keras

deep-learning

Votes: 0

Answers: 1

Latest Answer

You should redefine the input layer also in the Joint model def Joint(): input_autoencoder = layers.Input(shape=(256, 256, 5)) ### define input layer layer_autoencoder = Autoencoder()(input_auto...
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Marco Cerliani

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