Instructions to use InfiniAILab/CodeDrafter-500M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use InfiniAILab/CodeDrafter-500M with Transformers:

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

pipe = pipeline("text-generation", model="InfiniAILab/CodeDrafter-500M")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("InfiniAILab/CodeDrafter-500M")
model = AutoModelForCausalLM.from_pretrained("InfiniAILab/CodeDrafter-500M", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use InfiniAILab/CodeDrafter-500M with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "InfiniAILab/CodeDrafter-500M"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "InfiniAILab/CodeDrafter-500M",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/InfiniAILab/CodeDrafter-500M

SGLang

How to use InfiniAILab/CodeDrafter-500M 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 "InfiniAILab/CodeDrafter-500M" \
    --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": "InfiniAILab/CodeDrafter-500M",
		"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 "InfiniAILab/CodeDrafter-500M" \
        --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": "InfiniAILab/CodeDrafter-500M",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use InfiniAILab/CodeDrafter-500M with Docker Model Runner:
```
docker model run hf.co/InfiniAILab/CodeDrafter-500M
```

CodeDrafter-500M / README.md

Zhuoming Chen

Update README.md

f005f14 verified over 1 year ago

preview code

Raw

History Blame Contribute Delete

784 Bytes

metadata

license: apache-2.0
datasets:
  - iamtarun/python_code_instructions_18k_alpaca
  - angie-chen55/python-github-code
  - jtatman/python-code-dataset-500k
language:
  - en
base_model:
  - facebook/layerskip-llama3.2-1B
library_name: transformers
tags:
  - code

Model Card for CodeDrafter-500M

A draft model for Llama3.1/3.2/3.3 series models, specialized in python coding. This model is finetuned from the first 4 layers of facebook/layerskip-llama3.2-1B.

Citation

@article{chen2024sequoia,
  title={Sequoia: Scalable, Robust, and Hardware-aware Speculative Decoding},
  author={Chen, Zhuoming and May, Avner and Svirschevski, Ruslan and Huang, Yuhsun and Ryabinin, Max and Jia, Zhihao and Chen, Beidi},
  journal={arXiv preprint arXiv:2402.12374},
  year={2024}
}