Instructions to use kd13/RoPERT-MLM-mini with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kd13/RoPERT-MLM-mini with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="kd13/RoPERT-MLM-mini", trust_remote_code=True)# Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("kd13/RoPERT-MLM-mini", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e36a48f1326a577dbbaaa7bd3d6c6075791acc2c4b787c1638125bc8123d3523
- Size of remote file:
- 83.3 MB
- SHA256:
- 19c03d833407c6c1355deb49e17e506656d5d6005aa7e173753760fb000f991f
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