Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_model243 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_model243 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_model243")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_model243") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_model243", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 385631875d5e9889b400a063959ac8bde5818b21eeb6548e2c3acd45e155d071
- Size of remote file:
- 5.37 kB
- SHA256:
- c8376395e0ca92e7c573a4ea0a1827df3daaf7a096b0d02596a1414ab92c42e4
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.