Instructions to use KM4STfulltext/CSSCI_ABS_roberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KM4STfulltext/CSSCI_ABS_roberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="KM4STfulltext/CSSCI_ABS_roberta")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("KM4STfulltext/CSSCI_ABS_roberta") model = AutoModelForMaskedLM.from_pretrained("KM4STfulltext/CSSCI_ABS_roberta", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7e86716a8cd8602ebca4fb5655ce25c0c98e8f433e42d7e7979a2a14580bb1ab
- Size of remote file:
- 409 MB
- SHA256:
- 4af971e6271089431c54e0f7942dcaec64e8f7bb73b1234ed944404d7a8b7493
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.