Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_model261 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_model261 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_model261")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_model261") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_model261", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7a6aa8e407af8fccc995d32c4c6a27e9e405ad73d596086087d559eb14426e19
- Size of remote file:
- 5.37 kB
- SHA256:
- e954e403030cd9f1b6290b74566a69b931db0b44147314b41186c75782e53e99
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