Instructions to use vlsb/autotrain-security-text-classification-albert-688320769 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vlsb/autotrain-security-text-classification-albert-688320769 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="vlsb/autotrain-security-text-classification-albert-688320769")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("vlsb/autotrain-security-text-classification-albert-688320769") model = AutoModelForSequenceClassification.from_pretrained("vlsb/autotrain-security-text-classification-albert-688320769", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from vlsb/autotrain-security-text-classification-albert-688320769: direct link, hf CLI and curl.
- Browser
- Download file 46.8 MB
-
https://huggingface.co/vlsb/autotrain-security-text-classification-albert-688320769/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://vlsb/autotrain-security-text-classification-albert-688320769/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/vlsb/autotrain-security-text-classification-albert-688320769/resolve/main/pytorch_model.bin
46.8 MB
- Xet hash:
- 60acf5267f07c8aee4057b0442f1cf18f69ab34c68f31a6ef977dc0abc4340c5
- Size of remote file:
- 46.8 MB
- SHA256:
- d592fd43674b648564d783d038305c72ec3e12f2c22eadca7f915cb7318f8fed
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