Instructions to use bigcode/tiny_starcoder_py with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use bigcode/tiny_starcoder_py with Transformers:

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

pipe = pipeline("text-generation", model="bigcode/tiny_starcoder_py")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("bigcode/tiny_starcoder_py")
model = AutoModelForCausalLM.from_pretrained("bigcode/tiny_starcoder_py")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use bigcode/tiny_starcoder_py with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/bigcode/tiny_starcoder_py

SGLang

How to use bigcode/tiny_starcoder_py 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 "bigcode/tiny_starcoder_py" \
    --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": "bigcode/tiny_starcoder_py",
		"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 "bigcode/tiny_starcoder_py" \
        --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": "bigcode/tiny_starcoder_py",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use bigcode/tiny_starcoder_py with Docker Model Runner:
```
docker model run hf.co/bigcode/tiny_starcoder_py
```

Can you publish a javascript version?

by deleted - opened May 24, 2023

Discussion

deleted

May 24, 2023

It looks good, but would be more useful on my case if it were JavaScript! Thanks :)

loubnabnl

BigCode org May 25, 2023

We didn't train a JavaScript version, we might train slightly larger models which support the same programming languages as StarCoder in the future.

deleted

May 25, 2023

•

edited May 25, 2023

I see, problem of bigger multilanguage models is that it consume too many resources to run locally. Is there any chance you can train a JavaScript model just like this one?

Bilibili

May 30, 2023

We didn't train a JavaScript version, we might train slightly larger models which support the same programming languages as StarCoder in the future.

That would be really nice! A good balance between multiple language support/performance and model size is really important for democratic AI!

noobmldude

Sep 1, 2023

If I have to train a Javascript model for tiny_starcoder, is there any code that I can take a look at?
Do you use the same MegatronLM repo for training tiny_starcoder too with a smaller GPT2 model as base?

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