Text Generation
Transformers
Safetensors
slonik
code
postgresql
software-engineering
reinforcement-learning
Instructions to use dglhf/Slonik with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dglhf/Slonik with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="dglhf/Slonik")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("dglhf/Slonik", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use dglhf/Slonik with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "dglhf/Slonik" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "dglhf/Slonik", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/dglhf/Slonik
- SGLang
How to use dglhf/Slonik 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 "dglhf/Slonik" \ --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": "dglhf/Slonik", "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 "dglhf/Slonik" \ --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": "dglhf/Slonik", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use dglhf/Slonik with Docker Model Runner:
docker model run hf.co/dglhf/Slonik
Download NOTICE from dglhf/Slonik: direct link, hf CLI and curl.
- Browser
- Download file 730 Bytes
-
https://huggingface.co/dglhf/Slonik/resolve/main/NOTICE
- Command line
-
hf download hf://dglhf/Slonik/NOTICE
-
curl -L -o NOTICE https://huggingface.co/dglhf/Slonik/resolve/main/NOTICE
730 Bytes
| Slonik | |
| Copyright 2026 Postgres Professional. | |
| Slonik-27B is derived from Qwen/Qwen3.8-27B. | |
| Slonik-9B is derived from Qwen/Qwen3.5-9B. | |
| The upstream models are distributed under the Apache License, Version 2.0. | |
| Their license files are retained in licenses/Qwen3.8-27B/LICENSE and | |
| licenses/Qwen3.5-9B/LICENSE. | |
| Postgres Professional modified the model parameters through continued | |
| pretraining, supervised fine-tuning and reinforcement learning. | |
| The Apache License, Version 2.0 applies to the released model weights, | |
| configuration files and accompanying loading examples. The report and | |
| illustrations are separate materials; this notice does not relicense them. | |
| Embedded third-party fonts retain the licenses supplied under assets/. | |