Instructions to use iashour/CANDLE_cvss_availability with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use iashour/CANDLE_cvss_availability with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="iashour/CANDLE_cvss_availability")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("iashour/CANDLE_cvss_availability") model = AutoModelForSequenceClassification.from_pretrained("iashour/CANDLE_cvss_availability", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7a15b14f7a196753151d57ef9d3e4b92d326b0fe84b31aa245aa5d16e0647ce7
- Size of remote file:
- 438 MB
- SHA256:
- 9f42f6539b001b19f28dfe228fcdc1418239ed2ef59b59bdb37ea3694d6394f3
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