Text Classification
Transformers
TensorBoard
Safetensors
modernbert
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_model90 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_model90 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_model90")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_model90") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_model90", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 587cdb8727c8b6ca261a0c491318a110c5c4f1b37433d43923ed3a42ea747814
- Size of remote file:
- 5.37 kB
- SHA256:
- b56a3701bd34dfbc14a901f41f06cf7d325039754bfe715dd9284410ab0375d5
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.