Instructions to use Ahmade/dummu2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ahmade/dummu2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Ahmade/dummu2")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Ahmade/dummu2") model = AutoModel.from_pretrained("Ahmade/dummu2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cdc0f792fc1b490f106c6c981e33cd06f5bf0127e6573d25b3e60db2c1f8b797
- Size of remote file:
- 438 MB
- SHA256:
- e2055370d2ff32b2f7aebf62aba53f65dacdbe339167b3d9f41dbbb67e0c8375
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