Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_model239 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_model239 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_model239")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_model239") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_model239", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c0a584731167728c94ffcaebc87ca7f8534f73710482707533a47e2df1957a54
- Size of remote file:
- 5.37 kB
- SHA256:
- 01a52da62b1a1d51d3c158664b07b033173160628b3e097f740843b5c18b69f9
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