Instructions to use Falah/stable_diffusion_prompts with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Falah/stable_diffusion_prompts with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Falah/stable_diffusion_prompts")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Falah/stable_diffusion_prompts") model = AutoModelForCausalLM.from_pretrained("Falah/stable_diffusion_prompts") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use Falah/stable_diffusion_prompts with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Falah/stable_diffusion_prompts" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Falah/stable_diffusion_prompts", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Falah/stable_diffusion_prompts
- SGLang
How to use Falah/stable_diffusion_prompts 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 "Falah/stable_diffusion_prompts" \ --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": "Falah/stable_diffusion_prompts", "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 "Falah/stable_diffusion_prompts" \ --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": "Falah/stable_diffusion_prompts", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Falah/stable_diffusion_prompts with Docker Model Runner:
docker model run hf.co/Falah/stable_diffusion_prompts
- Xet hash:
- bcfa9a1f9ed05227a21369e1471404cbf9f14da005e7052f715c9cfea0210d29
- Size of remote file:
- 3.58 kB
- SHA256:
- 5310be362bae28e17949479d8a4b0856014bd92acec15c143e7fc033358902a7
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