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 model.safetensors from davidgaofc/ShadowAttackF: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/davidgaofc/ShadowAttackF/resolve/main/model.safetensors
- Command line
-
hf download hf://davidgaofc/ShadowAttackF/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/davidgaofc/ShadowAttackF/resolve/main/model.safetensors
268 MB
- Xet hash:
- 47407b8781ba2ba36c51fce570982eb4fd1d883f8b8ac755a6f1edbc12d24586
- Size of remote file:
- 268 MB
- SHA256:
- a89dd7e0cfc55690aa3809947ff7ed2d35fecca4f37cd588578731a5c895e91a
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