Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_model302 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_model302 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_model302")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_model302") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_model302", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 51f805329f1b51d77b0076657e2f5982fe94ec12b4f1efee43baa7ef37c103c9
- Size of remote file:
- 5.37 kB
- SHA256:
- de9753c4e0b5456917b853cb82983c3952a297b448b08ad62bd210d43a383435
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