Fairseq library This function generates a random dictionary with a specified number of tokens and saves it to a file. Dictionaries are commonly used data structures in natural language processing, which map words to unique integer indices. The type of code 2024-12-16 12:17:11 32 views
Fairseq Dictionary This function randomly selects an input text from the Fairseq model and translates it using a pretrained model. First, it loads the target dictionary, then tokenizes the input text, loads the pretrained model, performs the translation, and decodes the output tokens back into text. The type of code 2024-12-16 12:17:09 28 views
Fairseq PyTorch This function uses Fairseq library's models and datasets for random translation. It first randomly selects a model and corpus, then loads the model and dataset, and finally translates the input sentence. The type of code 2024-12-16 12:15:39 26 views
Fairseq PyTorch This code defines a function that uses the Fairseq library to generate random sentences between a given source and target language. It first loads the dictionaries and the model, then generates a random sample and uses the generator to produce the sentence. The type of code 2024-12-16 12:11:57 5 views
Fairseq PyTorch This function simulates generating a random sentence from a source language to a target language using functionalities from the Fairseq library such as model loading, translation, and data processing. Function 2024-12-16 12:11:19 5 views
Fairseq Dictionary This function uses the Fairseq library's Dictionary and FairseqModel to randomly encode and decode a given text using Byte Pair Encoding (BPE). It first loads the dictionary and model, then encodes the text into tokens from the dictionary, randomly shuffles these tokens, and finally decodes the shuffled tokens back into a string. The type of code 2024-12-16 12:07:09 4 views
Fairseq Dictionary This function uses the Fairseq library's model and dictionary to generate a random translation. It first loads the dictionary and the model, then tokenizes the source sentence, uses the model to generate the translation, and finally decodes the output tokens into a sentence. Translation generation 2024-12-16 12:06:38 11 views
Fairseq FairseqModel This function uses a Fairseq model and tokenizer to generate a random sentence. It initializes a random token index, then continuously samples tokens from the model, converts them to words, and adds them to the sentence until the maximum length is reached or a special end token is encountered. Custom Function 2024-12-16 12:05:01 4 views
Fairseq This function uses the FairseqDataset and FairseqModel from the Fairseq library to generate a random model based on a specified dataset and architecture name. It first loads the specified dataset, then constructs the model. Fairseq model generation 2024-12-16 12:02:59 6 views
Fairseq Tokenizer This code defines a function that uses the Fairseq library to load a pre-trained language model, tokenize the input text, and generate corresponding word vector embeddings. The type of code 2024-12-16 12:00:33 4 views
