Instructions to use gianma/classifierDomAugmented with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gianma/classifierDomAugmented with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="gianma/classifierDomAugmented")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("gianma/classifierDomAugmented") model = AutoModelForSequenceClassification.from_pretrained("gianma/classifierDomAugmented", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from gianma/classifierDomAugmented: direct link, hf CLI and curl.
- Browser
- Download file 443 MB
-
https://huggingface.co/gianma/classifierDomAugmented/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://gianma/classifierDomAugmented/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/gianma/classifierDomAugmented/resolve/main/pytorch_model.bin
443 MB
- Xet hash:
- 0e2b1c5ddf57c504ebd7346143f9e0829c33f0d42169a7ef5e6b40db5aead92d
- Size of remote file:
- 443 MB
- SHA256:
- a345392246e300358568f8592cfd0f9373e3a30ba8d2e8aa4998075009bbd45b
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