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
Notebooks
Google Colab
Kaggle
Local Apps

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
```

rishdotblog commited on May 9, 2024

Commit

e446d89

verified ·

1 Parent(s): bba43d8

Update README.md

Browse files

Files changed (1) hide show

README.md +41 -1

README.md CHANGED Viewed

@@ -5,4 +5,44 @@ metrics:
 pipeline_tag: text-generation
 tags:
 - code
----

 pipeline_tag: text-generation
 tags:
 - code
+---
+A capable language model for text to SQL generation that is on-par with the most capable generalist frontier models.
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/603bbad3fd770a9997b57cb6/h52Z_OKYBaDDQMFZyU5pF.png)
+## Model Description
+Developed by: Defog, Inc
+Model type: [Text to SQL]
+License: [CC-by-SA-4.0]
+Finetuned from model: [Meta-Llama-3-8B-Instruct]
+## Demo Page
+[https://defog.ai/sqlcoder-demo/](https://defog.ai/sqlcoder-demo/)
+## Ideal prompt and inference parameters
+Set temperature to 0, and do not do sampling.
+### Prompt
+```
+<|begin_of_text|><|start_header_id|>user<|end_header_id|>
+Generate a SQL query to answer this question: `{user_question}`
+{instructions}
+DDL statements:
+{table_metadata_string}<|eot_id|><|start_header_id|>assistant<|end_header_id|>
+The following SQL query best answers the question `{user_question}`:
+```sql
+```
+## Evaluation
+This model was evaluated on SQL-Eval, a PostgreSQL based evaluation framework developed by Defog for testing and alignment of model capabilities.
+You can read more about the methodology behind SQLEval [here](https://defog.ai/blog/open-sourcing-sqleval/).
+## Contact
+Contact us on X at [@defogdata](https://twitter.com/defogdata), or on email at founders@defog.ai