Category : huggingface-transformers

model = AutoModelForTokenClassification.from_pretrained("dbmdz/bert-large-cased-finetuned-conll03-english") tokenizer = BertTokenizer.from_pretrained("bert-base-cased") from transformers import LukeTokenizer from transformers import PreTrainedTokenizerFast label_list = [ "O", # Outside of a named entity "B-MISC", # Beginning of a miscellaneous entity right after another miscellaneous entity "I-MISC", # Miscellaneous entity "B-PER", # Beginning of a person’s name right after another person’s name "I-PER", # Person’s ..

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In 1 code., I have uploaded hugging face ‘transformers.trainer.Trainer’ based model using save_pretrained() function In 2nd code, I want to download this uploaded model and use it to make predictions. I need help in this step – How to download the uploaded model & then make a prediction? Steps to create model: from transformers import ..

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In my env(colab) I need the following library. Here is the list : !pip install –quiet transformers==4.1.1 !pip install –quiet pytorch-lightning==1.1.3 #!pip install pytorch-lightning !pip install –quiet tokenizers==0.9.4 !pip install –quiet sentencepiece==0.1.94 !pip install torchtext==0.8.0 torch==1.7.1 pytorch-lightning==1.1.3 After I am importing FARMReader and TransformersReader from haystack library. Here is the code !pip install grpcio-tools==1.34.1 !pip ..

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am using Jupyter Lab to run. It has pre-installed tf2.3_py3.6 kernel installed in it. It has 2 GPUS in it. PyTorch Lightning Version (e.g., 1.3.0): ‘1.4.6’ PyTorch Version (e.g., 1.8): ‘1.6.0+cu101′ Python version: 3.6 OS (e.g., Linux): system=’Linux’ CUDA/cuDNN version: 11.2 How you installed PyTorch (conda, pip, source): pip I am saving the best model ..

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I encountered something similar to this: BERT tokenizer & model download The link above is about downloading the Bert model itself, but I would only like to use the Bert Tokenizer. Normally I could do it like this: from transformers import BertTokenizer bert_tokenizer_en = BertTokenizer.from_pretrained("bert-base-uncased") bert_tokenizer_de=BertTokenizer.from_pretrained("bert-base-german-cased") But I am running it remotely, so I can’t ..

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I’m pretty new in ML, NLP, Data Science, and so on. I know several services for text summarization, paraphrasing, but from what I learned – they give really different results based on which text their models were trained (news, reviews, etc.) This research led me to HuggingFace transformers and https://huggingface.co/mrm8488/distilroberta-finetuned-financial-news-sentiment-analysis model in particular. But the ..

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I have a dataset with 2 columns: token, sentence. For example: {‘token’:’shrouded’, ‘sentence’:’A mist shrouded the sun’} I want to fine-tune one of the Huggingface Transformers model on a Masked Language Modelling task. (For now I am using distilroberta-base as per this tutorial) Now, instead of random masking, I am trying to specifically mask the ..

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I’m fine-tunning a BERT model using Hugging Face, Keras, Tensorflow libraries. Since yesterday I’m getting this error running my code in Google Colab. The odd thing is that the code used to run without any problem and suddenly started to throw this error. What is even more suspicious is that the code runs without problems ..

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