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:
- 0413e1da94ff0c73dbe98a944555cc7b039985b34f4b594671494eb7ca9633ad
- Size of remote file:
- 3.31 kB
- SHA256:
- 2a5bd23e6c586706fc70dfad4751c8d3173847382439d7afd74d51dfe92ae3c6
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