Instructions to use denritchie/tBERT-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use denritchie/tBERT-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="denritchie/tBERT-v1")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("denritchie/tBERT-v1") model = AutoModelForMaskedLM.from_pretrained("denritchie/tBERT-v1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0cbd926b37bcb8b4f6fb421c5f01dc48dafe95162a89dbda0c24dfed3907859c
- Size of remote file:
- 334 MB
- SHA256:
- 38ae2ebfe1f0119e0b14414f70a3ffeb0dae7e3f285809e5287ef333c3fd8952
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