Instructions to use christofid/dapbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use christofid/dapbert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="christofid/dapbert")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("christofid/dapbert") model = AutoModelForMaskedLM.from_pretrained("christofid/dapbert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8214d1e35a7ee5dbfa4cdde065e6c9009fe54e5664cdb47df7a888b70fa39471
- Size of remote file:
- 438 MB
- SHA256:
- 1c7e5c8aca50dc68e2fbfb1816c6ef0e0f73e9d6ba3a19d4d4666224ae8ee1f3
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