Instructions to use sagnikrayc/bert-base-uncased-fever with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sagnikrayc/bert-base-uncased-fever with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sagnikrayc/bert-base-uncased-fever")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sagnikrayc/bert-base-uncased-fever") model = AutoModelForSequenceClassification.from_pretrained("sagnikrayc/bert-base-uncased-fever", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d7d4716657951c2b309456ec970451dfb1fcd1c8398a9d673b81e35d8550f8ae
- Size of remote file:
- 438 MB
- SHA256:
- c92faeb97ba57374ad45679774301848cbab0b6d0735ebd4bc8f47a63e52d2f1
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