Instructions to use JunHwi/p_encoder_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JunHwi/p_encoder_test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="JunHwi/p_encoder_test")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("JunHwi/p_encoder_test") model = AutoModelForMaskedLM.from_pretrained("JunHwi/p_encoder_test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e82212f125caa9b286955c5b0ab653ed8012c4d4478bfa8235d6c86d2a43d2ce
- Size of remote file:
- 443 MB
- SHA256:
- 9fc64eb062099d456ef16a0f5e14706e1d1a2e42ed207a890981e3bbfe06c3f1
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