Instructions to use Kwai-AutoSQL/Kwai-AutoSQL-32B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Kwai-AutoSQL/Kwai-AutoSQL-32B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Kwai-AutoSQL/Kwai-AutoSQL-32B") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Kwai-AutoSQL/Kwai-AutoSQL-32B") model = AutoModelForCausalLM.from_pretrained("Kwai-AutoSQL/Kwai-AutoSQL-32B", device_map="auto") 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=256) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Kwai-AutoSQL/Kwai-AutoSQL-32B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Kwai-AutoSQL/Kwai-AutoSQL-32B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Kwai-AutoSQL/Kwai-AutoSQL-32B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Kwai-AutoSQL/Kwai-AutoSQL-32B
- SGLang
How to use Kwai-AutoSQL/Kwai-AutoSQL-32B 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 "Kwai-AutoSQL/Kwai-AutoSQL-32B" \ --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": "Kwai-AutoSQL/Kwai-AutoSQL-32B", "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 "Kwai-AutoSQL/Kwai-AutoSQL-32B" \ --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": "Kwai-AutoSQL/Kwai-AutoSQL-32B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use Kwai-AutoSQL/Kwai-AutoSQL-32B with Docker Model Runner:
docker model run hf.co/Kwai-AutoSQL/Kwai-AutoSQL-32B
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5c3f38a 3700f4c 5c3f38a 3700f4c | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | ---
license: apache-2.0
library_name: transformers
---
# Kwai-AutoSQL-32B
This repository only contains fine-tuned model weights, without training and inference scripts.
## Base Model
Original base model: Qwen/Qwen3-32B
The base model is released under Apache License 2.0.
## License Statement
1. All model weights, config.json, tokenizer files and all model binary assets in this repo are derivative works of Qwen/Qwen3-32B, governed by Apache License 2.0.
Copyright 2024 Alibaba Cloud
2. Repository descriptive documentation (README.md) and the root LICENSE file are licensed under MIT License.
Full MIT license text can be found in the root `LICENSE` file.
Copyright (c) 2026 Kuaishou Business Team |