Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_model253 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_model253 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_model253")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_model253") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_model253", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8c132b114ffad9fc690ade7f3757513cf17493b6d755fb45ec5eef7d3f610dee
- Size of remote file:
- 5.37 kB
- SHA256:
- 94f4817377e59812b0afc9c66e6e234978059d2e9b31605515746c8d65e0c476
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