Text Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_classifier_bsample_102 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_102 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_102")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_102") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_102", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3b4e9c24fa6d9e6dba02b7f9bd5de1c5e9f4e1bb6a69fe9a2770eff3d2fb9da6
- Size of remote file:
- 1.11 GB
- SHA256:
- a4acac35e34a28087bf4aef5c4764000c2d8acb09ed949449b926bce7b1f5dd4
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.