Instructions to use Chinook416/caracat_code with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Chinook416/caracat_code with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Chinook416/caracat_code")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Chinook416/caracat_code", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Chinook416/caracat_code with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Chinook416/caracat_code" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Chinook416/caracat_code", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Chinook416/caracat_code
- SGLang
How to use Chinook416/caracat_code 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 "Chinook416/caracat_code" \ --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": "Chinook416/caracat_code", "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 "Chinook416/caracat_code" \ --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": "Chinook416/caracat_code", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Chinook416/caracat_code with Docker Model Runner:
docker model run hf.co/Chinook416/caracat_code
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Copyright 2026 Caracat Code Project
This product includes software developed by the Caracat Code Project.
================================================================================
Base model attribution
================================================================================
Caracat Code is based on Qwen3-Coder-Next by Qwen.
Upstream model Qwen/Qwen3-Coder-Next
Upstream URL https://huggingface.co/Qwen/Qwen3-Coder-Next
Upstream license Apache License 2.0, as listed on the Hugging Face model
page. See THIRD_PARTY_LICENSES.md for the current
verification status of this statement.
Caracat Code was not trained from scratch. It derives from the upstream model
named above.
Any copyright notices, license notices, NOTICE files and attribution
information distributed with the upstream model must be preserved in every
redistribution of that material, including redistribution in modified form, as
required by the Apache License 2.0.
================================================================================
Scope of this NOTICE
================================================================================
The Apache License 2.0 in the LICENSE file of this repository applies to the
original source code authored for this project (training tooling, evaluation
tooling, configuration and documentation in this repository).
It does not, by itself, grant any rights in the upstream model weights. Those
remain governed by the license under which Qwen distributes them.
Third-party components and their licenses are listed in
THIRD_PARTY_LICENSES.md.
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