Instructions to use jparmet/topic-model-new-labels with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jparmet/topic-model-new-labels with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import BertClassifier model = BertClassifier.from_pretrained("jparmet/topic-model-new-labels", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from jparmet/topic-model-new-labels: direct link, hf CLI and curl.
- Browser
- Download file 4.09 kB
-
https://huggingface.co/jparmet/topic-model-new-labels/resolve/main/training_args.bin
- Command line
-
hf download hf://jparmet/topic-model-new-labels/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/jparmet/topic-model-new-labels/resolve/main/training_args.bin
4.09 kB
- Xet hash:
- 961bd1e1db5359de2fea47578af48359a54757920654de24f358caf28f7a0969
- Size of remote file:
- 4.09 kB
- SHA256:
- 44054d788b6ce4d194398c6b310767c6816802a9f9a94c668bafdf3be45b8074
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