Instructions to use TransWiC/bert-large-B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TransWiC/bert-large-B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="TransWiC/bert-large-B")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("TransWiC/bert-large-B") model = AutoModelForSequenceClassification.from_pretrained("TransWiC/bert-large-B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 725bdcdabcefbc6b976d39281b155a9f6745a980e5c99d3b238b532b11687701
- Size of remote file:
- 1.33 GB
- SHA256:
- 1dcaf7215ae85d4838a1f607f549c9eafc8171920e465240f4650d3be6cf98d6
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