Text Classification
Transformers
PyTorch
Safetensors
English
roberta
situation-entities
discourse-modes
clause-classification
narrativity
argumentation
text-embeddings-inference
Instructions to use BabakScrapes/disco-se-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BabakScrapes/disco-se-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="BabakScrapes/disco-se-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("BabakScrapes/disco-se-classifier") model = AutoModelForSequenceClassification.from_pretrained("BabakScrapes/disco-se-classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 06d3a339a41a865f9767349f63d5aaec1e93fcf655fbd05c5329f9b1768c7f90
- Size of remote file:
- 499 MB
- SHA256:
- 0264121801784420a0c3a505f66e36b94b32c1f13b2952e6f921e818b57153ff
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.