Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_model229 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_model229 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_model229")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_model229") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_model229", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7bba793a84396bad512bf7afd840b42f9b5d4ea795afb1b7f2fa4cac9282f8b7
- Size of remote file:
- 5.37 kB
- SHA256:
- d3b501ad63bd205a99e689a70e0ac9570498fabf0be7031ef8d59da27ae7acca
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