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:
- 3397b678066b3620c21df20b8b541e6ddf4a10c9259fa2fdf68264e4543145c4
- Size of remote file:
- 3.48 GB
- SHA256:
- 8890e67ff5e7849ac67c82a5fe3088c782f25b6b8224943a94a612014a413a5f
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