Instructions to use leomaurodesenv/bert-base-uncased-answerable-or-not-augmented with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use leomaurodesenv/bert-base-uncased-answerable-or-not-augmented with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="leomaurodesenv/bert-base-uncased-answerable-or-not-augmented")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("leomaurodesenv/bert-base-uncased-answerable-or-not-augmented") model = AutoModelForSequenceClassification.from_pretrained("leomaurodesenv/bert-base-uncased-answerable-or-not-augmented", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bddc826c43a8535c73d16f6f84c612c89cdea34bb5876b4c242a028446a1347b
- Size of remote file:
- 5.27 kB
- SHA256:
- 34af56a3462bee6ff37a1b794f1af5de74c6dadf8d9034c732a42eb71bf20947
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