Instructions to use sofom/bert-base-uncased-multitudev2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sofom/bert-base-uncased-multitudev2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sofom/bert-base-uncased-multitudev2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sofom/bert-base-uncased-multitudev2") model = AutoModelForSequenceClassification.from_pretrained("sofom/bert-base-uncased-multitudev2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4e566b06366668f47c45acf2a23765e55e44aaa9a67c44eb61e5b862a0c7714f
- Size of remote file:
- 219 MB
- SHA256:
- fc875a1a4e1e8dd178983457ff99e54feb58bc85ce2c8d1085e240605540ecb5
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