Instructions to use jashdalvi/netnames-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jashdalvi/netnames-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jashdalvi/netnames-classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jashdalvi/netnames-classifier") model = AutoModelForSequenceClassification.from_pretrained("jashdalvi/netnames-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from jashdalvi/netnames-classifier: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/jashdalvi/netnames-classifier/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://jashdalvi/netnames-classifier@refs/pr/1/pytorch_model.bin
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curl -L -o pytorch_model.bin https://huggingface.co/jashdalvi/netnames-classifier/resolve/refs%2Fpr%2F1/pytorch_model.bin
268 MB
- Xet hash:
- f540bead931a2943a76ef1079a64e9235af8ac959360b01dac1706f9482e5d0b
- Size of remote file:
- 268 MB
- SHA256:
- 5371f2ff63dcd2542ff4d394d39a39f594b45fa769ab98d91f7f5c0cffc4228d
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