Instructions to use SirWaffle/codegen-350M-multi-onnx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use SirWaffle/codegen-350M-multi-onnx with Transformers:

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

pipe = pipeline("text-generation", model="SirWaffle/codegen-350M-multi-onnx")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("SirWaffle/codegen-350M-multi-onnx")
model = AutoModelForCausalLM.from_pretrained("SirWaffle/codegen-350M-multi-onnx")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use SirWaffle/codegen-350M-multi-onnx with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "SirWaffle/codegen-350M-multi-onnx"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "SirWaffle/codegen-350M-multi-onnx",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/SirWaffle/codegen-350M-multi-onnx

SGLang

How to use SirWaffle/codegen-350M-multi-onnx 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 "SirWaffle/codegen-350M-multi-onnx" \
    --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": "SirWaffle/codegen-350M-multi-onnx",
		"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 "SirWaffle/codegen-350M-multi-onnx" \
        --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": "SirWaffle/codegen-350M-multi-onnx",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use SirWaffle/codegen-350M-multi-onnx with Docker Model Runner:
```
docker model run hf.co/SirWaffle/codegen-350M-multi-onnx
```

codegen-350M-multi-onnx

Commit History

Merge branch 'main' of https://huggingface.co/senior/codegen-350M-multi-onnx

b21152f

SirWaffle commited on Sep 5, 2022

Create README.md

fde2903

SirWaffle commited on Sep 5, 2022

added vocab/tokenizer related files

979c6d5

SirWaffle commited on Sep 4, 2022

initial onnx model commit

65e175c

SirWaffle commited on Aug 22, 2022

initial commit

46ed7a5

SirWaffle commited on Aug 22, 2022

Commit History

Merge branch 'main' of https://huggingface.co/senior/codegen-350M-multi-onnx b21152f

Create README.md fde2903

added vocab/tokenizer related files 979c6d5

initial onnx model commit 65e175c

initial commit 46ed7a5

Merge branch 'main' of https://huggingface.co/senior/codegen-350M-multi-onnx

b21152f

Create README.md

fde2903

added vocab/tokenizer related files

979c6d5

initial onnx model commit

65e175c

initial commit

46ed7a5