Instructions to use deshan/ro_schema with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deshan/ro_schema with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="deshan/ro_schema")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("deshan/ro_schema") model = AutoModelForMaskedLM.from_pretrained("deshan/ro_schema", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c8fe32780c85f58f6ef824ac9c346f55d551b3ab36c1f4ece94a0bfa13f6d971
- Size of remote file:
- 1.55 GB
- SHA256:
- 7e4eb64f3953c8eafa306b218532720f3fd552e85916d97e1f957c8587f1ba4f
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