Text Classification
Transformers
TensorBoard
Safetensors
deberta-v2
Trained with AutoTrain
text-embeddings-inference
Instructions to use idobn/twitter-mbti-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use idobn/twitter-mbti-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="idobn/twitter-mbti-v2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("idobn/twitter-mbti-v2") model = AutoModelForSequenceClassification.from_pretrained("idobn/twitter-mbti-v2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 29e6924af740ad913389bc71698d87d62793c13f5b0f62a97eac0382b8062dc5
- Size of remote file:
- 5.37 kB
- SHA256:
- 9a02b0d078d86ef0a1711524deea83d7a31c2e9047f6f3914251d4766e478633
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