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/310ccb2f3151bbd991ddc497dbf00a5ea11f34e7/pytorch_model.bin
- Command line
-
hf download hf://gianma/classifierDomAugmented@310ccb2f3151bbd991ddc497dbf00a5ea11f34e7/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/gianma/classifierDomAugmented/resolve/310ccb2f3151bbd991ddc497dbf00a5ea11f34e7/pytorch_model.bin
443 MB
- Xet hash:
- 591629c2ea565591f2972587ad30af128fedc6add137478a49cfe6a8365249f2
- Size of remote file:
- 443 MB
- SHA256:
- 41c06c53384705e8a7c282d5a4199f59494c3eb2c86096e01ba023de2a451979
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