---
license: apache-2.0
language:
- en
tags:
- legal
- contract-analysis
- legal-reasoning
- mistral
- olaverse
pipeline_tag: text-generation
library_name: transformers
base_model: unsloth/mistral-7b-v0.3-bnb-4bit
---

# Legal-Peace-7B-v1.0 🏛️⚖️

> ⚠️ **Beta Model**: This model is experimental and intended for research purposes. Outputs must always be reviewed by a qualified legal professional. Not recommended for production use.

**Legal-Peace-7B-v1.0** is a fine-tuned **Mistral-7B-v0.3** model designed for contract analysis and legal reasoning tasks.

Part of the [Olaverse Legal](https://github.com/Olaverse-Labs/olaverse)

## Quick Start

### Via the `olaverse` library (recommended)

```bash
pip install olaverse[legal]
```

```python
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
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

| Benchmark | Improvement |
|---|---|
| Inference Speed | ⚡ 10.3% faster (9.27s vs 10.33s) |
| Contract Analysis | 📋 32.6% faster |
| Case Predictions | ⚖️ 14.0% faster |
| Response Quality | 📝 More structured, professional legal responses |

## Model Details

| Property | Value |
|---|---|
| Base Model | Mistral-7B-v0.3 |
| Parameters | 7B |
| Quantization | 4-bit (unsloth BnB) |
| Training | SFT (4,800 cases) + DPO (419 legal reasoning examples) |
| License | Apache 2.0 |

## 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](https://github.com/Olaverse-Labs/olaverse)
- [Olaverse Library Docs](https://Olaverse-Labs.github.io/olaverse/)
- [Benchmarks](https://github.com/Olaverse-Labs/olaverse)

---

**Made with ❤️ by Olaverse AI**