Instructions to use q-future/q-align-aesthetic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use q-future/q-align-aesthetic with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="q-future/q-align-aesthetic")# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("q-future/q-align-aesthetic", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use q-future/q-align-aesthetic with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "q-future/q-align-aesthetic" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "q-future/q-align-aesthetic", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/q-future/q-align-aesthetic
- SGLang
How to use q-future/q-align-aesthetic 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 "q-future/q-align-aesthetic" \ --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": "q-future/q-align-aesthetic", "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 "q-future/q-align-aesthetic" \ --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": "q-future/q-align-aesthetic", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use q-future/q-align-aesthetic with Docker Model Runner:
docker model run hf.co/q-future/q-align-aesthetic
- Xet hash:
- 25a440064f692e15ae1ed86f286d8d095fc931b12e726280b3ebb9071c51ffe6
- Size of remote file:
- 5.82 kB
- SHA256:
- 7856f10dced9b738747de0778111758817b9148d68291dbe19f396c78a6f1a79
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