Instructions to use ShengdingHu/sst2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ShengdingHu/sst2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="ShengdingHu/sst2")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("ShengdingHu/sst2") model = AutoModelForMaskedLM.from_pretrained("ShengdingHu/sst2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9b276e7cdcf024736075fe07030820e7af09d84617fecb6083ea1886162ce2dd
- Size of remote file:
- 3.18 MB
- SHA256:
- 5774127d73c9e1df8a6076b5791a2acdcaa88b8799f6f13ea6187db6e089f1c3
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