Text Classification
Transformers
PyTorch
English
bert
Generated from Trainer
text-embeddings-inference
Instructions to use clincolnoz/bert-base-uncased-edos with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use clincolnoz/bert-base-uncased-edos with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="clincolnoz/bert-base-uncased-edos")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("clincolnoz/bert-base-uncased-edos") model = AutoModelForSequenceClassification.from_pretrained("clincolnoz/bert-base-uncased-edos", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bceed5544ae9f94607e172150b03d9dba1c4a7b07640742422a212fe622a941d
- Size of remote file:
- 3.58 kB
- SHA256:
- d641973e448ee0f5cd30cee300ef688f8e2706b6569a9d4b8a510df14f066454
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