Instructions to use AnonymousCS/populism_classifier_bsample_365 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_365 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_365")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_365") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_365", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 89afda5569582d97211666ec68c64963fdc77350fd93fad3210f9c88c2df5bc7
- Size of remote file:
- 1.34 GB
- SHA256:
- faf7c9086cd4dcb4f821b9df35e04263776b14eeae8d2db76da68034b55e0b9c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.