Zero-Shot Classification
Transformers
Safetensors
English
qwen3_5
feature-extraction
legal
decision-model
system-one
classification
citator
case-law
custom_code
Instructions to use jonathankleiman/lev with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jonathankleiman/lev with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="jonathankleiman/lev", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("jonathankleiman/lev", trust_remote_code=True) model = AutoModel.from_pretrained("jonathankleiman/lev", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update model card and report
Browse files- README.md +1 -1
- lev-technical-report.pdf +2 -2
README.md
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- **Excerpts hide things.** Lev sees the paragraphs around a citation, not the decision. Positive treatment in particular is often only visible from how the rest of the decision uses the case, and two careful readers of the same decision agree that a case was followed or applied only about half the time.
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- **It classifies an excerpt; it is not a citator.** It does not find citations, resolve them to cases, or check that the excerpt is complete. Treat its output as a lead to check against the decision. It is not legal advice.
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- **Images and video** are supported by the d3 runtime it inherits, but Lev was trained and tested on text only.
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- **Hosted baselines change.** Jev 1.13 and the OpenAI Decisions API (in public beta) were called
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## Files
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- **Excerpts hide things.** Lev sees the paragraphs around a citation, not the decision. Positive treatment in particular is often only visible from how the rest of the decision uses the case, and two careful readers of the same decision agree that a case was followed or applied only about half the time.
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- **It classifies an excerpt; it is not a citator.** It does not find citations, resolve them to cases, or check that the excerpt is complete. Treat its output as a lead to check against the decision. It is not legal advice.
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- **Images and video** are supported by the d3 runtime it inherits, but Lev was trained and tested on text only.
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- **Hosted baselines change.** Jev 1.13 and the OpenAI Decisions API (in public beta) were called on a single day.
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## Files
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lev-technical-report.pdf
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