Instructions to use ania3000/glot500-base-kuoss-morph with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ania3000/glot500-base-kuoss-morph with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ania3000/glot500-base-kuoss-morph")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("ania3000/glot500-base-kuoss-morph") model = AutoModelForTokenClassification.from_pretrained("ania3000/glot500-base-kuoss-morph", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9de2c520ac7240377871e22d03070d861108d2b3a549848e91c1e70a89c4141d
- Size of remote file:
- 26.9 MB
- SHA256:
- 2184548ae8e89465ec16369f7748821608b03c2d7f8953066e00364d8cc77028
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