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narcolepticchicken/
contract-drafter-v1

Name: contract-drafter-v1
Availability: InStock

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Contract Drafter v1

Fine-tuned Equall/Saul-7B-Instruct-v1 for legal contract clause drafting.

Training

Method: SFT + LoRA (r=16, alpha=32)
Examples: 126 across 9 contract types (SaaS, MSA, NDA, DPA, SOW, Vendor, Consulting, IP Assignment, Employment)
Epochs: 3
Learning rate: 2e-4 with cosine schedule
Final loss: 0.568 (down from 2.608)
Token accuracy: 96.9%

Usage

python

from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained(
    "narcolepticchicken/contract-drafter-v1",
    device_map="auto",
    torch_dtype="auto",
)
tokenizer = AutoTokenizer.from_pretrained("narcolepticchicken/contract-drafter-v1")

prompt = """<s>[INST] You are an expert contract drafter.

Draft a limitation_of_liability clause for a SaaS agreement.
Deal: Enterprise SaaS platform, $200K ACV, SOC 2 Type II.
Constraints: annual billing, 99.9% uptime SLA.
Law: Delaware

Draft ONLY the clause text. [/INST]"""

inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
outputs = model.generate(**inputs, max_new_tokens=600, temperature=0.3)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))

Performance

Evaluated against base model on 7 contract types. See contract-drafts-v1 for full results.

Files

model.safetensors — merged weights (3.8GB, 4-bit)
lora/ — LoRA adapter for future fine-tuning
tokenizer.json — SaulLM tokenizer (Mistral-based)

contract-drafting-assistant Space — interactive drafting UI
contract-clause-index-v1 — 37,508 real contract clauses
contract-nli-v1 — legal-domain NLI model

narcolepticchicken/contract-drafter-v1