Instructions to use giltack/distil-qwen3-4b-text2sql with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use giltack/distil-qwen3-4b-text2sql with Transformers:

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

pipe = pipeline("text-generation", model="giltack/distil-qwen3-4b-text2sql")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("giltack/distil-qwen3-4b-text2sql")
model = AutoModelForCausalLM.from_pretrained("giltack/distil-qwen3-4b-text2sql")
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 giltack/distil-qwen3-4b-text2sql with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "giltack/distil-qwen3-4b-text2sql"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "giltack/distil-qwen3-4b-text2sql",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/giltack/distil-qwen3-4b-text2sql

SGLang

How to use giltack/distil-qwen3-4b-text2sql 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 "giltack/distil-qwen3-4b-text2sql" \
    --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": "giltack/distil-qwen3-4b-text2sql",
		"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 "giltack/distil-qwen3-4b-text2sql" \
        --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": "giltack/distil-qwen3-4b-text2sql",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use giltack/distil-qwen3-4b-text2sql with Docker Model Runner:
```
docker model run hf.co/giltack/distil-qwen3-4b-text2sql
```

distil-qwen3-4b-text2sql / Modelfile

giltack

Duplicate from distil-labs/distil-qwen3-4b-text2sql

6f2835b 3 months ago

raw

history blame contribute delete

1.42 kB


	FROM ./model.gguf

	TEMPLATE """{{- $lastUserIdx := -1 -}}
	{{- range $idx, $msg := .Messages -}}
	{{- if eq $msg.Role "user" }}{{ $lastUserIdx = $idx }}{{ end -}}
	{{- end }}
	{{- if or .System .Tools }}<\|im_start\|>system
	{{ if .System }}{{ .System }}

	{{ end }}
	{{- if .Tools }}# Tools

	You may call one or more functions to assist with the user query.

	You are provided with function signatures within <tools></tools> XML tags:
	<tools>
	{{- range .Tools }}
	{"type": "function", "function": {{ .Function }}}
	{{- end }}
	</tools>

	For each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:
	<tool_call>
	{"name": <function-name>, "arguments": <args-json-object>}
	</tool_call>
	{{- end -}}
	<\|im_end\|>
	{{ end }}
	{{- range $i, $_ := .Messages }}
	{{- $last := eq (len (slice $.Messages $i)) 1 -}}
	{{- if eq .Role "user" }}<\|im_start\|>user
	{{ .Content }}<\|im_end\|>
	{{ else if eq .Role "assistant" }}<\|im_start\|>assistant
	{{ if .Content }}{{ .Content }}{{ end }}
	{{- if .ToolCalls }}
	{{- range .ToolCalls }}
	<tool_call>
	{"name": "{{ .Function.Name }}", "arguments": {{ .Function.Arguments }}}
	</tool_call>
	{{- end }}
	{{- end }}{{ if not $last }}<\|im_end\|>
	{{ end }}
	{{- else if eq .Role "tool" }}<\|im_start\|>user
	<tool_response>
	{{ .Content }}
	</tool_response><\|im_end\|>
	{{ end }}
	{{- if and (ne .Role "assistant") $last }}<\|im_start\|>assistant
	{{ end }}
	{{- end }}"""