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explosion/spaCy: v3.3.0: Improved speed, new trainable lemmatizer, and pipelines for Finnish, Korean and Swedish ...
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explosion/spaCy: v3.3.0: Improved speed, new trainable lemmatizer, and pipelines for Finnish, Korean and Swedish ...
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huggingface/transformers: v4.4.0: S2T, M2M100, I-BERT, mBART-50, DeBERTa-v2, XLSR-Wav2Vec2 ...
Abstract: v4.4.0: S2T, M2M100, I-BERT, mBART-50, DeBERTa-v2, XLSR-Wav2Vec2 SpeechToText Two new models are released as part of the S2T implementation: Speech2TextModel and Speech2TextForConditionalGeneration , in PyTorch. Speech2Text is a speech model that accepts a float tensor of log-mel filter-bank features extracted from the speech signal. It's a transformer-based seq2seq model, so the transcripts/translations are generated autoregressively. The Speech2Text model was proposed in fairseq S2T: Fast Speech-to-Text Modeling with fairseq by Changhan Wang, Yun Tang, Xutai Ma, Anne Wu, Dmytro Okhonko, Juan Pino. Compatible checkpoints can be found on the Hub: https://huggingface.co/models?filter=speech_to_text Speech2TextTransformer #10175 (@patil-suraj) M2M100 Two new models are released as part of the M2M100 implementation: M2M100Model and M2M100ForConditionalGeneration , in PyTorch. M2M100 is a multilingual encoder-decoder (seq-to-seq) model primarily intended for translation tasks. The M2M100 model was proposed in ...
URL: https://zenodo.org/record/4608351
https://dx.doi.org/10.5281/zenodo.4608351
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explosion/spaCy: v3.2.0: Registered scoring functions, Doc input, floret vectors and more ...
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5
Comparing the Effect of Product-Based Metrics on the Translation Process
In: Front Psychol (2021)
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huggingface/transformers: ProphetNet, Blenderbot, SqueezeBERT, DeBERTa ...
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huggingface/transformers: Trainer, TFTrainer, Multilingual BART, Encoder-decoder improvements, Generation Pipeline ...
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