Instructions to use arunmcops/LegalParam-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use arunmcops/LegalParam-GGUF with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf arunmcops/LegalParam-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf arunmcops/LegalParam-GGUF:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf arunmcops/LegalParam-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf arunmcops/LegalParam-GGUF:Q4_K_M
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf arunmcops/LegalParam-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf arunmcops/LegalParam-GGUF:Q4_K_M
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf arunmcops/LegalParam-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf arunmcops/LegalParam-GGUF:Q4_K_M
Use Docker
docker model run hf.co/arunmcops/LegalParam-GGUF:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use arunmcops/LegalParam-GGUF with Ollama:
ollama run hf.co/arunmcops/LegalParam-GGUF:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use arunmcops/LegalParam-GGUF with Docker Model Runner:
docker model run hf.co/arunmcops/LegalParam-GGUF:Q4_K_M
- Lemonade
How to use arunmcops/LegalParam-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull arunmcops/LegalParam-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.LegalParam-GGUF-Q4_K_M
List all available models
lemonade list
- Atomic Chat
LegalParam — GGUF
Legal · Indian Jurisprudence | BharatGenAI | हिन्दी + English
LegalParam is BharatGenAI's Indian legal domain specialist, trained on the Constitution of India, central and state acts, landmark Supreme Court and High Court judgments, IPC/BNS, CrPC/BNSS, and legal procedures.
Available Quantizations
| Quantization | File | Size | Description |
|---|---|---|---|
| F16 | LegalParam-F16.gguf |
~5.7 GB | Full float 16, near-lossless, GPU recommended |
| Q2_K | LegalParam-Q2_K.gguf |
~0.9 GB | 2-bit, smallest, significant quality loss |
| Q3_K_M | LegalParam-Q3_K_M.gguf |
~1.3 GB | 3-bit medium, moderate quality |
| Q4_K_M | LegalParam-Q4_K_M.gguf |
~1.7 GB | 4-bit medium — recommended for most users |
| Q5_K_M | LegalParam-Q5_K_M.gguf |
~2.0 GB | 5-bit medium, great quality |
| Q6_K | LegalParam-Q6_K.gguf |
~2.4 GB | 6-bit, excellent quality |
| Q8_0 | LegalParam-Q8_0.gguf |
~3.0 GB | 8-bit, best quality/size balance |
Not sure which to pick? → Q4_K_M for everyday use on CPU/GPU → Q8_0 for best quality on GPU with ≥ 6 GB VRAM → F16/BF16 for full precision research use
Use Cases
- Indian constitutional law queries
- IPC/BNS and CrPC/BNSS section lookup
- Landmark Supreme Court judgment summaries
- Legal rights advisory for citizens
- Contract and property law guidance
Quick Start
llama.cpp
# Windows
winget install llama.cpp
# Run directly from Hugging Face
llama-cli -hf arunmcops/LegalParam-GGUF:LegalParam-Q4_K_M.gguf
# OpenAI-compatible server
llama-server -hf arunmcops/LegalParam-GGUF:LegalParam-Q4_K_M.gguf --port 8080
Ollama
ollama run hf.co/arunmcops/LegalParam-GGUF:LegalParam-Q4_K_M.gguf
Python (llama-cpp-python)
from llama_cpp import Llama
llm = Llama.from_pretrained(
repo_id="arunmcops/LegalParam-GGUF",
filename="LegalParam-Q4_K_M.gguf",
)
response = llm.create_chat_completion(
messages=[{"role": "user", "content": "नमस्ते! आप कौन हैं?"}]
)
print(response["choices"][0]["message"]["content"])
About BharatGenAI
BharatGenAI builds open-source language models for India — bilingual (Hindi + English) and domain-specialized for agriculture, healthcare, legal, and general-purpose use.
- HuggingFace: arunmcops
License
Apache 2.0 — free for personal, research, and commercial use.
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