Instructions to use shailja/GPTJ_355M_Code with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use shailja/GPTJ_355M_Code with Transformers:

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

pipe = pipeline("text-generation", model="shailja/GPTJ_355M_Code")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("shailja/GPTJ_355M_Code")
model = AutoModelForCausalLM.from_pretrained("shailja/GPTJ_355M_Code")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use shailja/GPTJ_355M_Code with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "shailja/GPTJ_355M_Code"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "shailja/GPTJ_355M_Code",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/shailja/GPTJ_355M_Code

SGLang

How to use shailja/GPTJ_355M_Code 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 "shailja/GPTJ_355M_Code" \
    --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": "shailja/GPTJ_355M_Code",
		"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 "shailja/GPTJ_355M_Code" \
        --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": "shailja/GPTJ_355M_Code",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use shailja/GPTJ_355M_Code with Docker Model Runner:
```
docker model run hf.co/shailja/GPTJ_355M_Code
```

Finetuning Dataset and language?

by noobmldude - opened Jun 19, 2023

Discussion

noobmldude

Jun 19, 2023

Hi,
This looks interesting.
Would be very useful if you could share what is the dataset this is finetuned on.
and also since it mentions Code, which programming language code?
Thanks.

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