Instructions to use iashour/CANDLE_cvss_complexity with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use iashour/CANDLE_cvss_complexity with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="iashour/CANDLE_cvss_complexity")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("iashour/CANDLE_cvss_complexity") model = AutoModelForSequenceClassification.from_pretrained("iashour/CANDLE_cvss_complexity", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9d184775e61d0500d05c04c2652291dd1a9064a0e76e85f7de4cac984b246d81
- Size of remote file:
- 438 MB
- SHA256:
- 77c1667d9307fd89bc7a8e31f6d46be7a30b6ac0d723ae7d0a4b35d066a0234c
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