Instructions to use luffyAI/ChildModel-02 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use luffyAI/ChildModel-02 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="luffyAI/ChildModel-02")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("luffyAI/ChildModel-02") model = AutoModelForCausalLM.from_pretrained("luffyAI/ChildModel-02", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use luffyAI/ChildModel-02 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "luffyAI/ChildModel-02" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "luffyAI/ChildModel-02", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/luffyAI/ChildModel-02
- SGLang
How to use luffyAI/ChildModel-02 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 "luffyAI/ChildModel-02" \ --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": "luffyAI/ChildModel-02", "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 "luffyAI/ChildModel-02" \ --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": "luffyAI/ChildModel-02", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use luffyAI/ChildModel-02 with Docker Model Runner:
docker model run hf.co/luffyAI/ChildModel-02
Download pytorch_model.bin from luffyAI/ChildModel-02: direct link, hf CLI and curl.
- Browser
- Download file 5.3 GB
-
https://huggingface.co/luffyAI/ChildModel-02/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://luffyAI/ChildModel-02/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/luffyAI/ChildModel-02/resolve/main/pytorch_model.bin
5.3 GB
- Xet hash:
- dfb0d1d32d182189ef8b7c4d9212373ab6834a0653abbad9af9841b6c34dee3e
- Size of remote file:
- 5.3 GB
- SHA256:
- a51eb8d3e0dd49ba2db4b1f585b54b5dacccc586fe0c9383e02e27486774a817
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