Instructions to use BitanBiswas/deepD with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BitanBiswas/deepD with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="BitanBiswas/deepD")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("BitanBiswas/deepD") model = AutoModel.from_pretrained("BitanBiswas/deepD", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 24ff4660ad2b7038c5c92318ddeb3deee02b0faf08b115a035893d1a5f1e0e1a
- Size of remote file:
- 438 MB
- SHA256:
- a70633c79e15499b7a9d2035acd2cf59a1c420d402ab77ccefd3a47facf996c4
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