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
```

rvk7895 commited on Mar 14, 2024

Commit

bea9116

verified ·

1 Parent(s): 7c3da33

Update README.md

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@@ -14,14 +14,17 @@ tags:
 - basemodel
 - jax
 - pytorch
-- tensorflow
 - text-generation-inference
 library_name: transformers
 pipeline_tag: text-generation
 widget:
-- text: "<schema>CREATE TABLE system(JobID: String,GID: String, UID: String, Start:Time(yyyy/mm/dd), End: Time,ElapsedRaw: Time, CPUTimeRAW: Time,NCPUS: Number,NNodes: Number, NodeList: List,  State:String, Timelimit: Time);</schema><question>Get UID and job id for Jobs that started on Jan 20 , 2023 ended on feb 14 2023 and has job id 20</question><sql>"
-  example_title: "example"
 ---
 # pipSQL-1.3b
@@ -189,4 +192,4 @@ SELECT T1.customer_first_name ,  T1.customer_middle_initial ,  T1.customer_last_
 ```
 ### Team
-Avi Kothari, Pratham Gupta, Ritvik Aryan Kalra, Rohan Bhatial, Soham Acharya

 - basemodel
 - jax
 - pytorch
 - text-generation-inference
 library_name: transformers
 pipeline_tag: text-generation
 widget:
+- text: >-
+    <schema>CREATE TABLE system(JobID: String,GID: String, UID: String,
+    Start:Time(yyyy/mm/dd), End: Time,ElapsedRaw: Time, CPUTimeRAW: Time,NCPUS:
+    Number,NNodes: Number, NodeList: List,  State:String, Timelimit:
+    Time);</schema><question>Get UID and job id for Jobs that started on Jan 20
+    , 2023 ended on feb 14 2023 and has job id 20</question><sql>
+  example_title: example
 ---
 # pipSQL-1.3b
 ```
 ### Team
+Avi Kothari, Pratham Gupta, Ritvik Aryan Kalra, Rohan Bhatial, Soham Acharya