Text Classification
Transformers
TensorBoard
Safetensors
modernbert
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_model123 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_model123 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_model123")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_model123") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_model123", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from AnonymousCS/populism_model123: direct link, hf CLI and curl.
- Browser
- Download file 5.37 kB
-
https://huggingface.co/AnonymousCS/populism_model123/resolve/fea21e94de40ba91c71c2953127c9678264497ee/training_args.bin
- Command line
-
hf download hf://AnonymousCS/populism_model123@fea21e94de40ba91c71c2953127c9678264497ee/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/AnonymousCS/populism_model123/resolve/fea21e94de40ba91c71c2953127c9678264497ee/training_args.bin
5.37 kB
- Xet hash:
- 09cb16526360debe136d056103ef1dcb2746562ce2291742705b3f816bcc1663
- Size of remote file:
- 5.37 kB
- SHA256:
- 343cfbbe673b8df5be4cc0ab5f413815110cb084a610fe4a2e41b7ca4ae7749e
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