Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_model202 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_model202 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_model202")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_model202") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_model202", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9c0c92fc9ba0a753834df8520794eeeb5eee2e42a99d5566d166299b854a3586
- Size of remote file:
- 5.37 kB
- SHA256:
- 0d6911a745bcc693d591fa9172b1337cb54760b1ae760829e6d267dc80ae68f3
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