Instructions to use AnonymousCS/populism_model331 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_model331 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_model331")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_model331") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_model331", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from AnonymousCS/populism_model331: direct link, hf CLI and curl.
- Browser
- Download file 5.3 kB
-
https://huggingface.co/AnonymousCS/populism_model331/resolve/main/training_args.bin
- Command line
-
hf download hf://AnonymousCS/populism_model331/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/AnonymousCS/populism_model331/resolve/main/training_args.bin
5.3 kB
- Xet hash:
- 5c57e6641169c8170e2aafd56691ea512acd0d34209acbefc07423056e4262ef
- Size of remote file:
- 5.3 kB
- SHA256:
- 5cc18d46082e94c6d65886ea4910c3b22a24e7fc215a5907866419bba91ee9cc
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