Instructions to use iproskurina/tda-bert-en-cola with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use iproskurina/tda-bert-en-cola with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="iproskurina/tda-bert-en-cola")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("iproskurina/tda-bert-en-cola") model = AutoModelForSequenceClassification.from_pretrained("iproskurina/tda-bert-en-cola", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b9b1c038f9a0987f3a9b50db8c5051e7042564993172916744b1714a74bc9fec
- Size of remote file:
- 433 MB
- SHA256:
- ab1e967c968f80b1d99951fea971669fd641f68741264f16b2b0370bbc24dc74
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