Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_classifier_007 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_007 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_007")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_007") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_007", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 44ce9913f04dc263a0540ba523f52debbb67478cefc661dea15dcba0f49c8873
- Size of remote file:
- 5.78 kB
- SHA256:
- 60882667f6c9d8005d71beea045bb7cdbbb59610c2dcf46c9ec1e09b9a1535e7
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.