scottyjmp5/courtlistener-legal-corpus
Updated • 1.07k
A legal-domain fine-tune of huihui-ai/Huihui-Qwen3.6-27B-abliterated (an abliterated Qwen3.6-27B vision-language model), trained on 21k+ public-domain United States court opinions from CourtListener.
All base capabilities are preserved and were verified after merging: vision, tool/function calling, and thinking mode.
Fine-tuning teaches doctrine and style, not verbatim recall. Like every LLM, this model can hallucinate reporter citations, dates, and quotes. For any real legal-research use, run it with RAG over the CourtListener bulk data (or the linked training corpus) so citations come from retrieved documents. Verify every citation at the source before relying on it.
| Repo | Format | Size | For |
|---|---|---|---|
| this repo | bf16 safetensors | 52 GB | further fine-tuning, serving on 80GB+ |
| -FP8 | FP8 W8A8 (compressed-tensors) | 29 GB | vLLM on 40GB+ GPUs |
| -GGUF | Q4_K_M GGUF + vision projector | 16 GB | Ollama / llama.cpp on 24-32GB GPUs |
Download the GGUF variant files, then:
# Modelfile
FROM ./legal-27b.Q4_K_M.gguf
FROM ./legal-27b-mmproj.gguf
RENDERER qwen3.5
PARSER qwen3.5
ollama create legal-27b -f Modelfile
ollama run legal-27b
vllm serve scottyjmp5/Legal-Qwen3.6-27B-Abliterated-FP8 \
--trust-remote-code --max-model-len 8192