Instructions to use stabilityai/stablecode-completion-alpha-3b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use stabilityai/stablecode-completion-alpha-3b with Transformers:

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

pipe = pipeline("text-generation", model="stabilityai/stablecode-completion-alpha-3b")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("stabilityai/stablecode-completion-alpha-3b")
model = AutoModelForCausalLM.from_pretrained("stabilityai/stablecode-completion-alpha-3b")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use stabilityai/stablecode-completion-alpha-3b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "stabilityai/stablecode-completion-alpha-3b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "stabilityai/stablecode-completion-alpha-3b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/stabilityai/stablecode-completion-alpha-3b

SGLang

How to use stabilityai/stablecode-completion-alpha-3b 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 "stabilityai/stablecode-completion-alpha-3b" \
    --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": "stabilityai/stablecode-completion-alpha-3b",
		"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 "stabilityai/stablecode-completion-alpha-3b" \
        --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": "stabilityai/stablecode-completion-alpha-3b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use stabilityai/stablecode-completion-alpha-3b with Docker Model Runner:
```
docker model run hf.co/stabilityai/stablecode-completion-alpha-3b
```

ncoop57 commited on Aug 8, 2023

Commit

2fa8c56

1 Parent(s): 67bea8e

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@@ -78,4 +78,14 @@ StableCode-Completion-Alpha-3B independently generates new code completions, but
 ### Limitations and bias
-This model is intended to be used responsibly. It is not intended to be used to create unlawful content of any kind, to further any unlawful activity, or to engage in activities with a high risk of physical or economic harm.

 ### Limitations and bias
+This model is intended to be used responsibly. It is not intended to be used to create unlawful content of any kind, to further any unlawful activity, or to engage in activities with a high risk of physical or economic harm.
+## How to cite
+```bibtex
+@misc{StableCodeCompleteAlpha,
+      url={[https://huggingface.co/stabilityai/stablecode-complete-alpha-3b](https://huggingface.co/stabilityai/stablecode-complete-alpha-3b)},
+      title={Stable Code Complete Alpha},
+      author={Adithyan, Reshinth and Phung, Duy and Cooper, Nathan and Laforte, Christian}
+}
+```