Instructions to use TeamBlueEdifai/BERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TeamBlueEdifai/BERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="TeamBlueEdifai/BERT")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("TeamBlueEdifai/BERT") model = AutoModelForSequenceClassification.from_pretrained("TeamBlueEdifai/BERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 64dc9166d2df0e8ea991b7b4bccc7ee49848013abc8cba79177f9ce541e1bd6f
- Size of remote file:
- 5.24 kB
- SHA256:
- 8c2530b4b26f976a6c549f19eb5ada7a0fd13969a722ffe1c41476f0f80de978
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