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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6406c351c2384572c8f74499b7c4ecca10d4368862ba5f25120c698dfdec748e
- Size of remote file:
- 438 MB
- SHA256:
- 4e9f8d462d8d9118a72bd13f278e2a7f6f042f093ccece0b57016b19572f8c56
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