Instructions to use jasonwu/ToD-BERT-jnt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jasonwu/ToD-BERT-jnt with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="jasonwu/ToD-BERT-jnt")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("jasonwu/ToD-BERT-jnt") model = AutoModelForMaskedLM.from_pretrained("jasonwu/ToD-BERT-jnt", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from jasonwu/ToD-BERT-jnt: direct link, hf CLI and curl.
- Browser
- Download file 876 MB
-
https://huggingface.co/jasonwu/ToD-BERT-jnt/resolve/main/optimizer.pt
- Command line
-
hf download hf://jasonwu/ToD-BERT-jnt/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/jasonwu/ToD-BERT-jnt/resolve/main/optimizer.pt
876 MB
- Xet hash:
- beec4605f1720166261391c0a7c7a2d2a998d7038c256ea3ff7038ce99fc9388
- Size of remote file:
- 876 MB
- SHA256:
- a09ca179dd480f2cfca9894621ce83e4477f3aaa6c6fec5414e257925f5f059d
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