Instructions to use ahmedrizwan239/NativeSQL-with-schema with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use ahmedrizwan239/NativeSQL-with-schema with Transformers:

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

pipe = pipeline("text-generation", model="ahmedrizwan239/NativeSQL-with-schema")

# Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM

tokenizer = AutoTokenizer.from_pretrained("ahmedrizwan239/NativeSQL-with-schema")
model = AutoModelForSeq2SeqLM.from_pretrained("ahmedrizwan239/NativeSQL-with-schema")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use ahmedrizwan239/NativeSQL-with-schema with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "ahmedrizwan239/NativeSQL-with-schema"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ahmedrizwan239/NativeSQL-with-schema",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/ahmedrizwan239/NativeSQL-with-schema

SGLang

How to use ahmedrizwan239/NativeSQL-with-schema 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 "ahmedrizwan239/NativeSQL-with-schema" \
    --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": "ahmedrizwan239/NativeSQL-with-schema",
		"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 "ahmedrizwan239/NativeSQL-with-schema" \
        --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": "ahmedrizwan239/NativeSQL-with-schema",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use ahmedrizwan239/NativeSQL-with-schema with Docker Model Runner:
```
docker model run hf.co/ahmedrizwan239/NativeSQL-with-schema
```

ahmedrizwan239 commited on Feb 29, 2024

Commit

e0d76da

verified ·

1 Parent(s): 12bf3de

Update README.md

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README.md +13 -2

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@@ -1,6 +1,17 @@
 ---
-library_name: transformers
-tags: []
 ---
 # Model Card for Model ID

 ---
+language: en
+widget:
+  - text: >-
+      convert question and table into SQL query. tables: people_name(id,name),
+      people_age(people_id,age). question: how many people with name jui and age
+      less than 25
+license: cc-by-sa-4.0
+pipeline_tag: text2text-generation
+inference:
+  parameters:
+    max_length: 512
+    num_beams: 10
+    top_k: 10
 ---
 # Model Card for Model ID