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:
- f5a12221380a2369deab975c80ad57b1ddb7a5e600da2ffe3a4afb4284583ffb
- Size of remote file:
- 443 MB
- SHA256:
- 5348e12723963d6e652c488196f7f591d5e015effae3454f642475d3ac46f61d
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