Instructions to use arnolfokam/roberta-base-swa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use arnolfokam/roberta-base-swa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="arnolfokam/roberta-base-swa")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("arnolfokam/roberta-base-swa") model = AutoModelForTokenClassification.from_pretrained("arnolfokam/roberta-base-swa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 733034acfbadf5dd65b2c9f7695d0600eee46641f9a26506fc5cfa6388ab89d9
- Size of remote file:
- 1.46 kB
- SHA256:
- 8d19e27c754207ce11a3dc347d82948b6751e6e6daf946317a186607e00c295a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.