Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_model264 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_model264 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_model264")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_model264") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_model264", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7d750c47ef0b4355215040dea15cf9092f211eb070e8f791138ac56d2041ddfd
- Size of remote file:
- 5.37 kB
- SHA256:
- a85962c1c8782fd5538843c5b80f909efaf5dbf0df11349d812143ce3b5dad1e
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