Text Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_classifier_bsample_125 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_125 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_125")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_125") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_125", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d3e0f05159c8db32c27caadbd45e5d79954263007cdce937a46c83741fe33d68
- Size of remote file:
- 5.43 kB
- SHA256:
- c6c9706e56419325f51b771e2c4330bba9aedbf36e779f3b501f385da3f9423b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.