Web28 dec. 2024 · I have a situation where I am trying to using the pre-trained hugging-face models to translate a pandas column of text from Dutch to English. My input is simple: Dutch_text Hallo, het gaat goed ... that's correct I am using that model now as I am trying to translate text from german to english. WebConcluding, we can say we achieved our goal to create a non-English BERT-based text classification model. Our example referred to the German language but can easily be …
mrm8488/bert2bert_shared-german-finetuned-summarization
Web‘distilbert-base-german-cased’ is a correct model identifier listed on ‘Hugging Face – On a mission to solve NLP, one commit at a time. or ‘distilbert-base-german-cased’ is the … WebI would like to evaluate my model in any manner that is possible with my raw data, not having any labeled test data. I read something in Revisiting Correlations between … great inspection army
python - How do I interpret my BERT output from Huggingface ...
Web27 mrt. 2024 · Fortunately, hugging face has a model hub, a collection of pre-trained and fine-tuned models for all the tasks mentioned above. These models are based on a variety of transformer architecture – GPT, T5, BERT, etc. If you filter for translation, you will see there are 1423 models as of Nov 2024. Web18 aug. 2024 · Looking at the huggingface BertModel instructions here, which say: from transformers import BertTokenizer, BertModel tokenizer = BertTokenizer.from_pretrained ('bert-base-multilingual-cased') model = BertModel.from_pretrained ("bert-base-multilingual-cased") text = "Replace me by any text you'd like." WebTo do this, I am using huggingface transformers with tensorflow, more specifically the TFBertForSequenceClassification class with the bert-base-german-cased model (yes, … great inspection checklist army