Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_model262 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_model262 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_model262")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_model262") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_model262", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 14903e21dccac9397a12054507a481c1cafae99a99f9bb327915c1250e22be75
- Size of remote file:
- 5.37 kB
- SHA256:
- 6d7306adfc00a92c214c4a67738d9845cda1e51299e9128ad1be8e391883302d
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