Instructions to use peter2000/laya-vulnerability-groups-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use peter2000/laya-vulnerability-groups-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="peter2000/laya-vulnerability-groups-v2")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("peter2000/laya-vulnerability-groups-v2", device_map="auto") - Laya
How to use peter2000/laya-vulnerability-groups-v2 with Laya:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
Commit History
19 days ago
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Full accuracy+F1 metrics: laya v2 zero-shot, laya v2 fine-tuned, setfit (95 test rows)
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Pass HF_TOKEN to snapshot_download calls (authenticated resolve path)
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Full-metric eval script for v2: laya v2 zero-shot, laya v2 fine-tuned, setfit on the 95-row split
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Add evaluation metrics
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Laya v2 (climate-context instructions) fine-tuned on GIZ vulnerability data: macro-F1 0.704 (zero-shot 0.163)
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Fix UnboundLocalError: literal {label} inside write_readme f-string; reword v2-change sentence
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v2: label-aware climate-context instructions; otherwise identical RLCD recipe to v1
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initial commit
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