Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_model271 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_model271 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_model271")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_model271") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_model271", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8261af32881828bd0b8ea3a1c13e6763ca68cf41c79b4ede22cd1477e9330f20
- Size of remote file:
- 5.37 kB
- SHA256:
- 400d9b1a1d4faf47c7f7637361cfca044729b8b546c060050e73bc630a1e63a5
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