Instructions to use classla/bcms-bertic-parlasent-bcs-bi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use classla/bcms-bertic-parlasent-bcs-bi with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="classla/bcms-bertic-parlasent-bcs-bi")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("classla/bcms-bertic-parlasent-bcs-bi") model = AutoModelForSequenceClassification.from_pretrained("classla/bcms-bertic-parlasent-bcs-bi") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c1cc65cd9dfcdb677575162a6f7a0021e5fc6058f9248ad3dce5c7fd55ef2672
- Size of remote file:
- 3.18 kB
- SHA256:
- dacdcd47d12db8bb03062be59d936e32ffb31b98c337e79bc837125de08ac86f
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