Instructions to use christofid/dabert-multi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use christofid/dabert-multi with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="christofid/dabert-multi")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("christofid/dabert-multi") model = AutoModelForMaskedLM.from_pretrained("christofid/dabert-multi") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 950814ef616db3f08fca018ce0fc910a758f31e1659d6951b4c8d50e4df7bc82
- Size of remote file:
- 2.74 kB
- SHA256:
- 6398456dd958820e85510be37bdbaba275f3eaf37cd667a469d4b6fc5a2ad085
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