Instructions to use RedHatAI/starcoder2-15b-quantized.w8a16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use RedHatAI/starcoder2-15b-quantized.w8a16 with Transformers:

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

pipe = pipeline("text-generation", model="RedHatAI/starcoder2-15b-quantized.w8a16")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("RedHatAI/starcoder2-15b-quantized.w8a16")
model = AutoModelForCausalLM.from_pretrained("RedHatAI/starcoder2-15b-quantized.w8a16")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use RedHatAI/starcoder2-15b-quantized.w8a16 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "RedHatAI/starcoder2-15b-quantized.w8a16"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "RedHatAI/starcoder2-15b-quantized.w8a16",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/RedHatAI/starcoder2-15b-quantized.w8a16

SGLang

How to use RedHatAI/starcoder2-15b-quantized.w8a16 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 "RedHatAI/starcoder2-15b-quantized.w8a16" \
    --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": "RedHatAI/starcoder2-15b-quantized.w8a16",
		"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 "RedHatAI/starcoder2-15b-quantized.w8a16" \
        --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": "RedHatAI/starcoder2-15b-quantized.w8a16",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use RedHatAI/starcoder2-15b-quantized.w8a16 with Docker Model Runner:
```
docker model run hf.co/RedHatAI/starcoder2-15b-quantized.w8a16
```

Update README.md

by ReactionControl - opened Jan 6

base: refs/heads/main

←

from: refs/pr/1

Discussion Files changed

-0

ReactionControl

Jan 6

Dear repository author,
I wanted to take a moment to express how impressed I am with your model. It's truly outstanding and has shown great performance. I am writing to indicate my interest in contributing to the README of your model. Specifically, I would like to update the base_model information to enhance the documentation. This is to address the gap in the model card and ensure users have complete, accurate information.
Thank you for your attention to this matter.

Update README.mdb30239bd

alexmarques

Red Hat AI org Jan 6

Thanks for your contribution!

alexmarques changed pull request status to merged Jan 6

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