Instructions to use PathFinderKR/sparse-roberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PathFinderKR/sparse-roberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="PathFinderKR/sparse-roberta")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("PathFinderKR/sparse-roberta") model = AutoModelForMaskedLM.from_pretrained("PathFinderKR/sparse-roberta", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 14e96a3dbc70ef408466a0f15b8afa798a7fa9669f85ffed27272afa8c29ef05
- Size of remote file:
- 499 MB
- SHA256:
- d4262669625f9564d7da7b67cdc70bdbe087ae0b31e01eaace27197765ac660a
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