Fairseq TransformerModel This function uses the Transformer model from the Fairseq library to perform text translation. It first loads the pre-trained model and dictionary, then encodes the source text, translates it using the model, and finally decodes the translated tokens into text. Translation function 2024-12-16 12:17:55 34 views
Fairseq TransformerModel This function randomly selects TransformerModel and HubertTokenizer from the Fairseq library to translate input text into another language. The type of code 2024-12-16 12:15:22 24 views
Fairseq TransformerModel This code defines a function that uses a Transformer model from the Fairseq library to generate random translations from source tokens to target tokens. The function accepts lists of source and target tokens, as well as the path to the pretrained model. It loads the model, converts the tokens to tensors, and then uses the model to perform the translation. The type of code 2024-12-16 12:12:56 4 views
Fairseq TransformerModel This function uses the TransformerModel from the Fairseq library to generate a random translation from source text to target text. It first loads a pre-trained model, then encodes the source and target texts, translates them using the model, and finally decodes the output. The type of code 2024-12-16 12:10:13 4 views
Fairseq TransformerModel This function uses the Transformer model from the Fairseq library to translate text. It first randomly selects a model, then loads the model and the dictionary for the source language, translates the input text, and finally decodes the translated tokens back into text. Translation function 2024-12-16 12:01:55 5 views
Textual library This function uses Textual library's TransformerModel and TextDataset to generate a specified number of random sentences. It first loads a pre-trained model and then generates sentences based on the given seed. Function 2024-12-16 12:00:19 5 views
Fairseq TransformerModel This function uses the TransformerModel from the Fairseq library to generate a random sentence. It first initializes a random input tensor of the same size as the model's input embedding, then generates an output tensor through the model, and finally extracts the generated sentence by greedy decoding from the output. The type of code 2024-12-16 11:59:33 5 views
Fairseq TransformerModel This function uses the Fairseq library's Transformer model to obtain the embedding representation of a given word. It first checks if the provided model is an instance of TransformerModel, then moves the model to the specified device, and finally retrieves the embedding of the word through the model. The type of code 2024-12-16 11:57:16 4 views
Fairseq TransformerModel This function uses the Transformer model from the Fairseq library to generate a random sentence. It initializes an input with a start token and then continuously generates new tokens through the model until reaching the maximum length. Finally, it removes the padding token from the end of the generated sentence. Generate random sentences 2024-12-16 11:57:13 3 views
Fairseq TransformerModel This function uses the Transformer model from the Fairseq library to generate a random sentence. First, it ensures that the model is in evaluation mode, then it generates a random sequence of tokens, moves them to the correct device, and then translates using the model, finally returning the translation result. Function 2024-12-16 11:53:29 4 views
