Instructions to use defog/llama-3-sqlcoder-8b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use defog/llama-3-sqlcoder-8b with Transformers:

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

pipe = pipeline("text-generation", model="defog/llama-3-sqlcoder-8b")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("defog/llama-3-sqlcoder-8b")
model = AutoModelForCausalLM.from_pretrained("defog/llama-3-sqlcoder-8b")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Inference
Local Apps Settings

vLLM

How to use defog/llama-3-sqlcoder-8b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "defog/llama-3-sqlcoder-8b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "defog/llama-3-sqlcoder-8b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/defog/llama-3-sqlcoder-8b

SGLang

How to use defog/llama-3-sqlcoder-8b 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 "defog/llama-3-sqlcoder-8b" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "defog/llama-3-sqlcoder-8b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

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 "defog/llama-3-sqlcoder-8b" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "defog/llama-3-sqlcoder-8b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use defog/llama-3-sqlcoder-8b with Docker Model Runner:
```
docker model run hf.co/defog/llama-3-sqlcoder-8b
```

Is the sqlcoder model architecture supported by vllm?

by rparik - opened May 16, 2024

Discussion

rparik

May 16, 2024

•

edited May 16, 2024

Is the sqlcoder model architecture supported by vllm?
https://docs.vllm.ai/en/latest/models/supported_models.html

Not sure which artchitecture the vllm models fall under?

omeryentur

May 17, 2024

It needs to be supported because Llama 3 is a fine-tuned version. LlamaForCausalLM

rparik

May 17, 2024

Thanks! what about the old SQL coder models?
sql-coder-7b-2, sql-coder-70b-alpha, sql-coder-34b-alpha

omeryentur

May 17, 2024

•

edited May 17, 2024

You can find information in the Model Details section. CodeLlama-7B for sqlcoder-7b-2 which also falls into the llama type --> LlamaForCausalLM

wongjingping

May 18, 2024

•

edited May 18, 2024

Yes it is supported by vllm, and @omeryentur rightly pointed out that these belong to the Llama family of models. In addition, our public evaluation framework + dataset allow you to use VLLM as the runner (see https://github.com/defog-ai/sql-eval?tab=readme-ov-file#vllm)

wongjingping changed discussion status to closed May 18, 2024

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