Instructions to use KM4STfulltext/CSSCI_ABS_roberta_wwm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KM4STfulltext/CSSCI_ABS_roberta_wwm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="KM4STfulltext/CSSCI_ABS_roberta_wwm")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("KM4STfulltext/CSSCI_ABS_roberta_wwm") model = AutoModelForMaskedLM.from_pretrained("KM4STfulltext/CSSCI_ABS_roberta_wwm") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 04613a5b0140255048cd31074721069921b25f0fe76d409a8d117e332a17cb93
- Size of remote file:
- 409 MB
- SHA256:
- 825416b2a0eef6b3110be5ef097a65ba6d4d5596be63dee67f82bdbd31235879
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.