Instructions to use opencsg/opencsg-stable-code-3b-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use opencsg/opencsg-stable-code-3b-v1 with Transformers:

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

pipe = pipeline("text-generation", model="opencsg/opencsg-stable-code-3b-v1", trust_remote_code=True)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("opencsg/opencsg-stable-code-3b-v1", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use opencsg/opencsg-stable-code-3b-v1 with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/opencsg/opencsg-stable-code-3b-v1

SGLang

How to use opencsg/opencsg-stable-code-3b-v1 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 "opencsg/opencsg-stable-code-3b-v1" \
    --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": "opencsg/opencsg-stable-code-3b-v1",
		"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 "opencsg/opencsg-stable-code-3b-v1" \
        --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": "opencsg/opencsg-stable-code-3b-v1",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use opencsg/opencsg-stable-code-3b-v1 with Docker Model Runner:
```
docker model run hf.co/opencsg/opencsg-stable-code-3b-v1
```

TomPei commited on Mar 28, 2024

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@@ -128,9 +128,9 @@ print(tokenizer.decode(tokens[0], skip_special_tokens=True))
 </div>
-OpenCSG 致力于资源融合、软件求精和生成式 LM。其中，“C”代表资源融合（Converged resources），表示多种混合资源的整合和充分利用。 “S”代表软件求精（Software refinement），表示通过大模型精炼过的软件。 “G”代表生成型语言模型（Generative LM），它表示广泛使用的、包容性的、经过民主化的生成式大模型。
-OpenCSG 的愿景是让每个行业、每个公司、每个人都拥有自己的模型。 我们坚持开放开源的原则，将OpenCSG的大模型栈提供给社区。 欢迎大家积极使用、反馈想法和贡献内容。

 </div>
+OpenCSG中 Open是开源开放；C 代表 Converged resources，整合和充分利用的混合异构资源优势，算力降本增效；S 代表 Software refined，重新定义软件的交付方式，通过大模型驱动软件开发，人力降本增效；G 代表 Generative LM，大众化、普惠化和民主化的可商用的开源生成式大模型。
+OpenCSG的愿景是让每个行业、每个公司、每个人都拥有自己的模型。 我们坚持开源开放的原则，将OpenCSG的大模型软件栈开源到社区，欢迎使用、反馈和参与共建，欢迎关注。