Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_model296 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_model296 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_model296")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_model296") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_model296", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 078eb9828e3bf03136893e20fb46d1263c4fd46fb37119fd52e3119c8df43536
- Size of remote file:
- 5.37 kB
- SHA256:
- 8466c2fe98f6a44af0fb9666e39563bdec6c01eee2019581347393910471086d
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