Image-Text-to-Text
Transformers
Safetensors
GGUF
Japanese
English
qwen3_5
typed-decisions
classification
conversational
Instructions to use JurinAI/JJ-1-2B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JurinAI/JJ-1-2B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="JurinAI/JJ-1-2B") messages = [ { "role": "user", "content": [ {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"}, {"type": "text", "text": "What animal is on the candy?"} ] }, ] pipe(text=messages)# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("JurinAI/JJ-1-2B") model = AutoModelForMultimodalLM.from_pretrained("JurinAI/JJ-1-2B", device_map="auto") messages = [ { "role": "user", "content": [ {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"}, {"type": "text", "text": "What animal is on the candy?"} ] }, ] inputs = processor.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=256) print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use JurinAI/JJ-1-2B 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 JurinAI/JJ-1-2B:Q8_0 # Run inference directly in the terminal: llama cli -hf JurinAI/JJ-1-2B:Q8_0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf JurinAI/JJ-1-2B:Q8_0 # Run inference directly in the terminal: llama cli -hf JurinAI/JJ-1-2B:Q8_0
Build from source code
git clone https://github.com/ggml-org/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-app # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama serve -hf JurinAI/JJ-1-2B:Q8_0 # Run inference directly in the terminal: ./build/bin/llama cli -hf JurinAI/JJ-1-2B:Q8_0
Use Docker
docker model run hf.co/JurinAI/JJ-1-2B:Q8_0
- Llama new
- LM Studio
- Jan
- vLLM
How to use JurinAI/JJ-1-2B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "JurinAI/JJ-1-2B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "JurinAI/JJ-1-2B", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'Use Docker
docker model run hf.co/JurinAI/JJ-1-2B:Q8_0
- SGLang
How to use JurinAI/JJ-1-2B with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "JurinAI/JJ-1-2B" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "JurinAI/JJ-1-2B", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "JurinAI/JJ-1-2B" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "JurinAI/JJ-1-2B", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }' - Ollama
How to use JurinAI/JJ-1-2B with Ollama:
ollama run hf.co/JurinAI/JJ-1-2B:Q8_0
- Unsloth Desktop
- Pi
How to use JurinAI/JJ-1-2B with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf JurinAI/JJ-1-2B:Q8_0
Configure the model in Pi
# Install Pi: npm install -g @earendil-works/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "JurinAI/JJ-1-2B:Q8_0" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use JurinAI/JJ-1-2B with Docker Model Runner:
docker model run hf.co/JurinAI/JJ-1-2B:Q8_0
- Lemonade
How to use JurinAI/JJ-1-2B with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull JurinAI/JJ-1-2B:Q8_0
Run and chat with the model
lemonade run user.JJ-1-2B-Q8_0
List all available models
lemonade list
- Hermes Agent
How to use JurinAI/JJ-1-2B with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf JurinAI/JJ-1-2B:Q8_0
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default JurinAI/JJ-1-2B:Q8_0
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use JurinAI/JJ-1-2B with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf JurinAI/JJ-1-2B:Q8_0
Configure OpenClaw
# Install OpenClaw: npm install -g openclaw@latest # Register the local server and set it as the default model: openclaw onboard --non-interactive --mode local \ --auth-choice custom-api-key \ --custom-base-url http://127.0.0.1:8080/v1 \ --custom-model-id "JurinAI/JJ-1-2B:Q8_0" \ --custom-provider-id llama-cpp \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
File size: 1,763 Bytes
dbf752e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 | """Run the same Japanese request through Transformers or llama.cpp."""
import argparse
import json
from pathlib import Path
STATE = "洗面所の天井から水が落ち続けていて、床が水浸しです。至急見に来てください。"
QUESTIONS = {
"category": {
"type": "choice",
"instructions": "問い合わせの種類は?",
"criteria": {"water": "水漏れ", "noise": "騒音", "other": "その他"},
},
"needs_visit": {"type": "noul", "instructions": "現地での対応が必要ですか?"},
"urgency": {
"type": "score",
"instructions": "対応の緊急度は?",
"criteria": ["急がない", "数日以内", "今すぐ"],
},
}
def main():
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument("--backend", choices=["transformers", "gguf"], default="transformers")
parser.add_argument("--model", default=str(Path(__file__).resolve().parent))
parser.add_argument("--device", choices=["cpu", "cuda"], default="cpu")
parser.add_argument("--url", default="http://127.0.0.1:8081")
args = parser.parse_args()
if args.backend == "gguf":
from jj1 import GGUF
model = GGUF(args.model, url=args.url)
try:
answers, usage = model.decide(STATE, QUESTIONS)
finally:
model.close()
else:
import torch
from jj1 import JJ1
if args.device == "cpu":
torch.set_num_threads(4)
model = JJ1(args.model, images=False, device=args.device, max_length=4096)
answers, usage = model.decide(STATE, QUESTIONS)
print(json.dumps({"answers": answers, "usage": usage}, ensure_ascii=False, indent=2))
if __name__ == "__main__":
main()
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