Quick Start

Via the olaverse library (recommended)

bash
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pip install olaverse[legal]

python
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from olaverse.llm import LegalPeace

model = LegalPeace()  # defaults to "olaverse/legal-peace-v1.0"
model.load()          # requires GPU + unsloth

prompt = "Analyze this clause: 'All disputes shall be resolved through binding arbitration in Delaware.' What are the key implications?"
response = model.generate(prompt, max_new_tokens=300, temperature=0.7)
print(response)

Via Hugging Face directly

python
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from unsloth import FastLanguageModel

model, tokenizer = FastLanguageModel.from_pretrained(
    model_name="olaverse/legal-peace-v1.0",
    max_seq_length=2048,
    dtype=None,
    load_in_4bit=True,
)

FastLanguageModel.for_inference(model)

prompt = "Analyze this clause: 'All disputes shall be resolved through binding arbitration in Delaware.'"

inputs = tokenizer(prompt, return_tensors="pt").to("cuda")
outputs = model.generate(**inputs, max_new_tokens=300, temperature=0.7)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))

Performance vs Base Mistral-7B

Model Details

Use Cases

✅ Contract clause analysis and review ✅ Legal research assistance ✅ Evidence evaluation ✅ Case outcome prediction ✅ Legal Q&A

Limitations

⚠️ Beta model — not for production use ⚠️ Not a replacement for legal professionals ⚠️ Always verify outputs with qualified attorneys ⚠️ Trained primarily on U.S. legal data

Links

• GitHub
• Olaverse Library Docs
• Benchmarks

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