Instructions to use ielabgroup/ToRoDer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ielabgroup/ToRoDer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="ielabgroup/ToRoDer")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("ielabgroup/ToRoDer") model = AutoModelForMaskedLM.from_pretrained("ielabgroup/ToRoDer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 77f944f671170264173bfbea36682a0648eff2b55dc9344a4740e32ba7b3a236
- Size of remote file:
- 438 MB
- SHA256:
- 9c181bdd970bc24920c981584f6ed24a9bc3d1ae59dd8309ec1aebb6ffdb8165
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