Instructions to use arnolfokam/mbert-base-uncased-pcm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use arnolfokam/mbert-base-uncased-pcm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="arnolfokam/mbert-base-uncased-pcm")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("arnolfokam/mbert-base-uncased-pcm") model = AutoModelForTokenClassification.from_pretrained("arnolfokam/mbert-base-uncased-pcm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a0a2c9acb5d0937a5b9a33e1729a2a9f8a47d1ea66371bff680f94c539a95214
- Size of remote file:
- 709 MB
- SHA256:
- b1ddbd7fa3253e4ed6f825e2f7cf24d6d84f718ebecab87e238e00e80b0b7b8a
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