Instructions to use k-partha/decision_bert_bio with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use k-partha/decision_bert_bio with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="k-partha/decision_bert_bio")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("k-partha/decision_bert_bio") model = AutoModelForSequenceClassification.from_pretrained("k-partha/decision_bert_bio") - Notebooks
- Google Colab
- Kaggle
File size: 699 Bytes
4743acd 94d0dbd b3fc8ff 94d0dbd b3fc8ff 94d0dbd e886226 94d0dbd | 1 2 3 4 5 6 7 8 9 10 11 | Rates Twitter biographies on decision-making preference: Thinking or Feeling. Roughly corresponds to [agreeableness.](https://en.wikipedia.org/wiki/Agreeableness)
Go to your Twitter profile, copy your biography and paste in the inference widget, remove any URLs and press hit!
Trained on self-described personality labels. Interpret as a continuous score, not as a discrete label. Remember that models employ pure statistical reasoning (and may consequently make no sense sometimes.)
Have fun!
Note: Performance on inputs other than Twitter biographies [the training data source] is not verified.
For further details and expected performance, read the [paper](https://arxiv.org/abs/2109.06402). |