Instructions to use sofom/bert-base-uncased-mage with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sofom/bert-base-uncased-mage with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sofom/bert-base-uncased-mage")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sofom/bert-base-uncased-mage") model = AutoModelForSequenceClassification.from_pretrained("sofom/bert-base-uncased-mage") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 08e360cb0aabbb6eb44dad62954c363017c26bc1ca9eb28fa6da39312cb38112
- Size of remote file:
- 219 MB
- SHA256:
- b5e768b7dbefb4e387f03d6e7d6caf4366e6ac39a2f01657b59ab4b3cb2cebcb
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