Text Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_classifier_bsample_208 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_208 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_208")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_208") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_208", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 98930f7502ff96d0ada1f3d9de0630da7cc601adb4cbb01eddce963f8f426de9
- Size of remote file:
- 1.11 GB
- SHA256:
- fbf1cfe0f8b7eab934368862de0933b72c97195b548f463474fd655766a056c1
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.