Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_model166 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_model166 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_model166")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_model166") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_model166", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c2aee2ec8186bb9c4e1f3ace1d541f830f08ea290c9a6e852ce0072fac578d2c
- Size of remote file:
- 5.37 kB
- SHA256:
- dcadaf5dd156155854b07cb8c97b202e4d3cdb4f58460646b92232ef4f92f99c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.