Downloads · 30 days
25
24% of all-time downloads
xml_xnli__inclusiveORexclusive__binary_classification__frenchANDenglish
BeToast/xml_xnli__inclusiveORexclusive__binary_classification__frenchANDenglish
xml_xnli__inclusiveORexclusive__binary_classification__frenchANDenglish is a text classification model from BeToast. Use it when you need a label for a piece of text. It is set up for sentence-transformers. The card lists the license as apache-2.0.
This model is used for binary classification of racially/culturally exclusive or exclusive sentences in French and English languages. It is a fine-tuned model of morit/frenchxlmxnli on this dataset
All-time downloads
105
Public
Repo size
3.4 GB
Likes
1
Public
Repo makeup
Click a slice to open those files.
.bin1.1 GB · 98%
At a glance
- Task
- Text Classification
- Library
- sentence-transformers
- License
- apache-2.0
- Model type
- xlm-roberta
- Access
- Public
- Created
- Mar 31, 2023
- Updated
- Mar 31, 2023
- SHA
- e440ebe8
Try a prompt
Model card
From the Hugging Face model README
/content/model
This model is used for binary classification of racially/culturally exclusive or exclusive sentences in French and English languages.
It is a fine-tuned model of morit/french_xlm_xnli
on this dataset
with SetFit model
This model generalizes exclusivity well which is shown by the ability to detect exclusivity even to fictional races.
All code for entire experiments is in my gitrepo
Usage
Use example Google Collab notebook
Use this model in your own code:
python -m pip install setfit
You can then run predictions with the model:
from setfit import SetFitModel
# Download from Hub and run inference
model = SetFitModel.from_pretrained("/content/model")
# Run inclusive or exclusive binary classification.
predictions = model(["Elves are all snobs", "Elves are known for their high intelligence and wealth"])
predictions
- Task
- Text Classification
- Library
- sentence-transformers
- Type
- xlm-roberta
- License
- apache-2.0
- Created
- Mar 31, 2023
- Updated
- Mar 31, 2023