Text Classification
Transformers
PyTorch
TensorBoard
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use Shunian/mbti-classification-roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Shunian/mbti-classification-roberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Shunian/mbti-classification-roberta-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Shunian/mbti-classification-roberta-base") model = AutoModelForSequenceClassification.from_pretrained("Shunian/mbti-classification-roberta-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 193bc8a8e3064d35b0021502a5ea1824b5f8b65e63b30111d31a809c3f4f1865
- Size of remote file:
- 499 MB
- SHA256:
- f66ef04400c5038e073227ed9714079e19f20909f3ba4c45481d3fcd09a311c2
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