Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use Centipede5/mbti_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Centipede5/mbti_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Centipede5/mbti_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Centipede5/mbti_model") model = AutoModelForSequenceClassification.from_pretrained("Centipede5/mbti_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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update model card README.md
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End of training
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Training in progress, epoch 3
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Training in progress, epoch 2
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Training in progress, epoch 1
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initial commit
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