Instructions to use jumplander/jumplander-coder-32b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use jumplander/jumplander-coder-32b with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="jumplander/jumplander-coder-32b")

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("jumplander/jumplander-coder-32b", dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use jumplander/jumplander-coder-32b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "jumplander/jumplander-coder-32b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "jumplander/jumplander-coder-32b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/jumplander/jumplander-coder-32b

SGLang

How to use jumplander/jumplander-coder-32b 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 "jumplander/jumplander-coder-32b" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "jumplander/jumplander-coder-32b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

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 "jumplander/jumplander-coder-32b" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "jumplander/jumplander-coder-32b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use jumplander/jumplander-coder-32b with Docker Model Runner:
```
docker model run hf.co/jumplander/jumplander-coder-32b
```

🇮🇷 Future Access to Jumplander Models 🚀

by jumplander - opened Nov 21, 2025

Discussion

jumplander

Owner Nov 21, 2025

•

edited Nov 21, 2025

Hello friends! 👋
We are the Jumplander team and we’d like to share a bit about the current status of our models and our future plans.

Why are the models currently private? 🔒

Data protection and security 🛡️ – The models contain important team architectures and information that need protection.
Quality and optimization ⚡ – Before making them public, we ensure the models are fully stable and ready to use.
Support and user experience 📚 – Our goal is to provide full documentation and practical examples to deliver the best experience.

Future Access 🌟
In upcoming updates and new programs, we plan to make the models available locally for users.
This means you can run the models on your own system and fully leverage their capabilities without compromising security or quality.

We appreciate your patience ❤️ and are excited to make the Jumplander models accessible and enjoyable for all developers in Iran 🇮🇷.

For more information and to test the models, visit jumplander.org 🌐

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