Instructions to use PipableAI/pip-sql-1.3b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use PipableAI/pip-sql-1.3b with Transformers:

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

pipe = pipeline("text-generation", model="PipableAI/pip-sql-1.3b")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("PipableAI/pip-sql-1.3b")
model = AutoModelForCausalLM.from_pretrained("PipableAI/pip-sql-1.3b")
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]:]))

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use PipableAI/pip-sql-1.3b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "PipableAI/pip-sql-1.3b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "PipableAI/pip-sql-1.3b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/PipableAI/pip-sql-1.3b

SGLang

How to use PipableAI/pip-sql-1.3b 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 "PipableAI/pip-sql-1.3b" \
    --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": "PipableAI/pip-sql-1.3b",
		"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 "PipableAI/pip-sql-1.3b" \
        --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": "PipableAI/pip-sql-1.3b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use PipableAI/pip-sql-1.3b with Docker Model Runner:
```
docker model run hf.co/PipableAI/pip-sql-1.3b
```

How to best format a schema for pip-sql?

by misafu - opened Mar 11, 2024

Discussion

misafu

Mar 11, 2024

•

edited Mar 11, 2024

Hello, I'm having some difficulties sometimes getting joins between tables in the schema properly recognised sometimes.
Is there any documentation out there about how to best specify primary and foreign keys the schema?
From what I can see in the training data schemas those relationships aren't specified, and everything is either type integer or text.
Does that pattern need to be followed?
Thank you!

QagentS

Pipable Inc org Mar 11, 2024

•

edited Mar 11, 2024

Hi , we have mixed different prompt formats while training so as to ensure certain level of independence to prompt format. We will be releasing a new model next week where more type of instructions can be specified in pre prompt.
Adding as comment beside the col in prompt or adding instructions helps in many places right now.

QagentS

Pipable Inc org Mar 11, 2024

BTW if you would like to colab with us to tune the model on your schema with our RL algo we can help out as well. Usually works best in production deployment settings where it has seen some 30 -40 example queries of the schema during finetuning.

QagentS changed discussion status to closed Mar 11, 2024

pratham-pi changed discussion status to open Mar 11, 2024

pratham-pi changed discussion status to closed Mar 15, 2024

QagentS changed discussion status to open Mar 28, 2024

QagentS

Pipable Inc org Mar 28, 2024

Hi , try https://huggingface.co/PipableAI/pip-library-etl-1.3b .
Its more general purpose and can take instructions better.
If it does something wrong you can add that example in prompt and it will handle it's permutation type questions well. --qesution: --response:

avi-pipable changed discussion status to closed Apr 3, 2024

Upload images, audio, and videos by dragging in the text input, pasting, or clicking here.

Tap or paste here to upload images

· Sign up or log in to comment