Instructions to use ania3000/mmbert-base-kuoss-morph with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ania3000/mmbert-base-kuoss-morph with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ania3000/mmbert-base-kuoss-morph")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("ania3000/mmbert-base-kuoss-morph") model = AutoModelForTokenClassification.from_pretrained("ania3000/mmbert-base-kuoss-morph", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a28445f37ed617a0247665c10f916652e3c8f108f9a5cc6ec35a665e7afedac5
- Size of remote file:
- 5.84 kB
- SHA256:
- 1b2fa5d09dab2b33e0871e61e073afa80a95b8bf4473087a84b1d48965406388
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