Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_model259 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_model259 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_model259")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_model259") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_model259", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f1a40441ddab2e42b89152033b1f8e6404ba132a887159d8830144101e23306a
- Size of remote file:
- 5.37 kB
- SHA256:
- 669d8c01f9d77440a15ca23fc49f5e290d9f30a28b469ac15500f592066307d5
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