Instructions to use andreas122001/bloomz-3b-wiki-detector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use andreas122001/bloomz-3b-wiki-detector with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="andreas122001/bloomz-3b-wiki-detector")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("andreas122001/bloomz-3b-wiki-detector") model = AutoModelForSequenceClassification.from_pretrained("andreas122001/bloomz-3b-wiki-detector", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 64339dddb08690b643c074948b8da5e5ce6c47d115ff16cd98f5d920f5485ee8
- Size of remote file:
- 3.45 kB
- SHA256:
- a13f46516b66c4a30669d7ac24fe7bf8db7c77d8fae3472699544306334faf9d
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