Instructions to use michaelginn/treebert-pretrained-100k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use michaelginn/treebert-pretrained-100k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="michaelginn/treebert-pretrained-100k")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("michaelginn/treebert-pretrained-100k") model = AutoModelForMaskedLM.from_pretrained("michaelginn/treebert-pretrained-100k") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c5343f9792c18d7b6dd0a5dbb0cf9677352f8b7086d82362444aa7160e0196dc
- Size of remote file:
- 497 MB
- SHA256:
- 64f51da4ef28e99ba12b050465df6280b4fffe9f4318e9562db9b9f36bc4559c
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