Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use davidgaofc/temp_attack with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use davidgaofc/temp_attack with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="davidgaofc/temp_attack")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("davidgaofc/temp_attack") model = AutoModelForSequenceClassification.from_pretrained("davidgaofc/temp_attack", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 681e3103ec8d88302e9f0b9680c8271599b765c22bf818a300facfd10feb3520
- Size of remote file:
- 4.54 kB
- SHA256:
- 2888f45ca80c8915c7952b219f2e55f787d81f2cf5bfe85f691cd1f1b69243ae
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