Instructions to use while-ai/text-to-sql-shop-r5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use while-ai/text-to-sql-shop-r5 with PEFT:

from peft import PeftModel
from transformers import AutoModelForCausalLM

base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3-4B")
model = PeftModel.from_pretrained(base_model, "while-ai/text-to-sql-shop-r5")

Transformers

How to use while-ai/text-to-sql-shop-r5 with Transformers:

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

pipe = pipeline("text-generation", model="while-ai/text-to-sql-shop-r5")

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("while-ai/text-to-sql-shop-r5", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use while-ai/text-to-sql-shop-r5 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "while-ai/text-to-sql-shop-r5"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "while-ai/text-to-sql-shop-r5",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/while-ai/text-to-sql-shop-r5

SGLang

How to use while-ai/text-to-sql-shop-r5 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 "while-ai/text-to-sql-shop-r5" \
    --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": "while-ai/text-to-sql-shop-r5",
		"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 "while-ai/text-to-sql-shop-r5" \
        --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": "while-ai/text-to-sql-shop-r5",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use while-ai/text-to-sql-shop-r5 with Docker Model Runner:
```
docker model run hf.co/while-ai/text-to-sql-shop-r5
```

text-to-sql-shop-r5

Commit History

card: recipe and collection links

65a45c2
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whileai commited on 19 days ago

r5: LoRA adapter from run_4696a1c651ff26c7

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Zero Proof AI commited on 23 days ago

Upload README.md with huggingface_hub

bde0ee1
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Zero Proof AI commited on 23 days ago

initial commit

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Zero Proof AI commited on 23 days ago

Commit History

card: recipe and collection links 65a45c2 verified

r5: LoRA adapter from run_4696a1c651ff26c7 cbad4c1 verified

Upload README.md with huggingface_hub bde0ee1 verified

initial commit df2cd53 verified

card: recipe and collection links

65a45c2
verified

r5: LoRA adapter from run_4696a1c651ff26c7

cbad4c1
verified

Upload README.md with huggingface_hub

bde0ee1
verified

initial commit

df2cd53
verified