Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_model161 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_model161 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_model161")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_model161") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_model161", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e48b3b4b21e3a7df482f10a47ef76c72c557252c3a61a7fc4644d009193aa2a0
- Size of remote file:
- 5.37 kB
- SHA256:
- b59b2c7f89903628cd9b5e0104952ce283b41f788e53ee699f58b7044e4dd3b9
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