Text Classification
Transformers
Safetensors
English
bert
big-five
regression
psychology
transformer
text-analysis
Instructions to use vladinc/bigfive-regression-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vladinc/bigfive-regression-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="vladinc/bigfive-regression-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("vladinc/bigfive-regression-model") model = AutoModelForSequenceClassification.from_pretrained("vladinc/bigfive-regression-model") - Notebooks
- Google Colab
- Kaggle
Logits not between 0 and 1
#1
by JanMack - opened
Hi,
I tested the model and found that the output of the model for each property is not between 0 and 1.
I used the test code with the following results:
from transformers import AutoTokenizer, AutoModelForSequenceClassification
model = AutoModelForSequenceClassification.from_pretrained("vladinc/bigfive-regression-model")
tokenizer = AutoTokenizer.from_pretrained("vladinc/bigfive-regression-model")
text = "I enjoy reflecting on abstract concepts and trying new things."
inputs = tokenizer(text, return_tensors="pt")
outputs = model(**inputs)
print(outputs.logits) # Output: tensor([[4.3761, 3.5514, 3.5852, 3.7274, 2.3770]], grad_fn=)