Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use davidgaofc/ShadowAttackF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use davidgaofc/ShadowAttackF with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="davidgaofc/ShadowAttackF")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("davidgaofc/ShadowAttackF") model = AutoModelForSequenceClassification.from_pretrained("davidgaofc/ShadowAttackF", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from davidgaofc/ShadowAttackF: direct link, hf CLI and curl.
- Browser
- Download file 4.54 kB
-
https://huggingface.co/davidgaofc/ShadowAttackF/resolve/main/training_args.bin
- Command line
-
hf download hf://davidgaofc/ShadowAttackF/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/davidgaofc/ShadowAttackF/resolve/main/training_args.bin
4.54 kB
- Xet hash:
- 3ca4b84d002a09883730886610e63857ffd974ccc2d01779deb94ea454e94667
- Size of remote file:
- 4.54 kB
- SHA256:
- cc7b66625d7c777b9c86156ca9f1c348bac4365cd1d77b7fd1256d4bdbe572dd
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