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Questions - huggingface

For what is used parameter return_dict in BertModel?

I have something like this model=BertModel.from_pretrained('bert-base-uncased',return_dict=True) What exactly is this "return_dict" used for? What happens when True and what when False?
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Alem

nlp

bert-language-model

huggingface

Votes: 0

Answers: 1

Latest Answer

When instantiating a BertModel, the default output of the model when evaluating or predicting will be a tuple consisting of loss, logits, hidden_states and attentions. predictions = model(ids_tensor) ...
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furaharu

wandb getting logged without initiating

I do not want to use wandb. I don't even have an account. I am simply following this notebook for finetuning. I am not running the 2nd and 3 cells because I do not want to push the model to the hub. H...
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Kiera.K

huggingface-transformers

huggingface-tokenizers

fine-tune

wandb

huggingface

Votes: 0

Answers: 1

Latest Answer

posting the same message as over on transformers: You can turn off all external logger logging, including wandb logging by passing report_to="none" in your Seq2SeqTrainingArguments. You mig...
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morganmcg

Is there a way to load local csv.gz file in huggingface dataloader?

I'm using datasets library by huggingface to load csv dataset stored locally. The problem is, the dataset is compressed and is stored as a csv.gz file. Therefore, I'm not able to load it using load_da...
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Mahavir I

huggingface-datasets

huggingface

Votes: 0

Answers: 1

Latest Answer

Just decompress it with gunzip: gunzip -v yourdataset.csv.gz
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cronoik

HuggingFace FinBert Model in google Collab

When I run my FinBert model it always crashes the RAM in Google Collab at outputs = model(**input) from transformers.utils.dummy_pt_objects import HubertModel import textwrap # Reads all files at once...
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Vishrut Tiwari

python

huggingface-transformers

collaboration

huggingface

Votes: 0

Answers: 1

Latest Answer

You do text = list(headlines_array[:,0]) and then later, inputs = tokenizer(text, padding = True, truncation = True, return_tensors='pt') Hence, you give the tokenizer a list of text. It will return y...
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doguaraci

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