Instructions to use JanSt/albert-base-v2_mbti-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JanSt/albert-base-v2_mbti-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="JanSt/albert-base-v2_mbti-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("JanSt/albert-base-v2_mbti-classification") model = AutoModelForSequenceClassification.from_pretrained("JanSt/albert-base-v2_mbti-classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ed447660b4e9ae96d9edb9d7fc1056d8331d793e11fb0e5e7009f7b104471469
- Size of remote file:
- 3.5 kB
- SHA256:
- 89dbca91b1a91d9cc84ccf2eca657cabe66ae6337d1891e925c2989736e53cd1
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