Instructions to use whitedevil0089devil/cyber_bot1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use whitedevil0089devil/cyber_bot1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="whitedevil0089devil/cyber_bot1")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("whitedevil0089devil/cyber_bot1") model = AutoModelForSequenceClassification.from_pretrained("whitedevil0089devil/cyber_bot1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_data.json from whitedevil0089devil/cyber_bot1: direct link, hf CLI and curl.
- Browser
- Download file 173 MB
-
https://huggingface.co/whitedevil0089devil/cyber_bot1/resolve/9aa6c21fa9f8d9d8febc29fcd61ba3fc029944ca/training_data.json
- Command line
-
hf download hf://whitedevil0089devil/cyber_bot1@9aa6c21fa9f8d9d8febc29fcd61ba3fc029944ca/training_data.json
-
curl -L -o training_data.json https://huggingface.co/whitedevil0089devil/cyber_bot1/resolve/9aa6c21fa9f8d9d8febc29fcd61ba3fc029944ca/training_data.json
173 MB
- Xet hash:
- c4283951ae2d914755ba45c42337f51b456897a0eb644252ff18f5b3a07fcb47
- Size of remote file:
- 173 MB
- SHA256:
- 53406be56a0535c9cc8a4f7a2ab6ed9d4a7da5e46a5ed6fa2a72108f7e5d4a4d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.