Instructions to use AndyChiang/cdgp-csg-scibert-dgen with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AndyChiang/cdgp-csg-scibert-dgen with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="AndyChiang/cdgp-csg-scibert-dgen")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("AndyChiang/cdgp-csg-scibert-dgen") model = AutoModelForMaskedLM.from_pretrained("AndyChiang/cdgp-csg-scibert-dgen", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 11a8ec6daa5c868ac9860e065b7139b8dab0a0361abdf8e903f5da8075b41f71
- Size of remote file:
- 440 MB
- SHA256:
- fdd3ac54e832a2f5a7e0c196f4c931bfdb73a4ff0aa7a8038e919e2eaa85641b
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