Text Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_classifier_bsample_100 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_100 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_100")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_100") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_100", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4edf3a39a070d031adca97f92779ae12c629ef5ffde0f4e9db7dfe0924321a2d
- Size of remote file:
- 1.11 GB
- SHA256:
- df193085d4c949931f088763e53325a4476ac0639e61597bd6a3d6a66c6a24b3
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.