Instructions to use h4shk4t/darkpatternLLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use h4shk4t/darkpatternLLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="h4shk4t/darkpatternLLM")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("h4shk4t/darkpatternLLM") model = AutoModelForSequenceClassification.from_pretrained("h4shk4t/darkpatternLLM", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- eef545ea294bd520d19645b39442f335f03a2b7e67331b626e7d7ddf4e980708
- Size of remote file:
- 1.42 GB
- SHA256:
- e46791d401feb29262f9f026dd7662e639eaa15c05ad60aa3de1ca574d33d50c
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