Instructions to use sarkerlab/SocBERT-final with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sarkerlab/SocBERT-final with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="sarkerlab/SocBERT-final")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("sarkerlab/SocBERT-final") model = AutoModelForMaskedLM.from_pretrained("sarkerlab/SocBERT-final") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1dd7f333ae82c99e196534362166ac25f1451cd4cfee7169e0063b7691f971b9
- Size of remote file:
- 572 MB
- SHA256:
- f318e9f0b4f3b0f36663802bc17cf439f4cd15d14ca300fa2ef696ed249204fc
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