Text Generation
Transformers
Safetensors
English
gpt2
lyrics
suno
music
scansion
text-generation-inference
Instructions to use wren11ws/sunup with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wren11ws/sunup with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="wren11ws/sunup")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("wren11ws/sunup") model = AutoModelForCausalLM.from_pretrained("wren11ws/sunup", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use wren11ws/sunup with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "wren11ws/sunup" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "wren11ws/sunup", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/wren11ws/sunup
- SGLang
How to use wren11ws/sunup 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 "wren11ws/sunup" \ --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": "wren11ws/sunup", "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 "wren11ws/sunup" \ --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": "wren11ws/sunup", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use wren11ws/sunup with Docker Model Runner:
docker model run hf.co/wren11ws/sunup
Download generation_config.json from wren11ws/sunup: direct link, hf CLI and curl.
- Browser
- Download file 228 Bytes
-
https://huggingface.co/wren11ws/sunup/resolve/main/generation_config.json
- Command line
-
hf download hf://wren11ws/sunup/generation_config.json
-
curl -L -o generation_config.json https://huggingface.co/wren11ws/sunup/resolve/main/generation_config.json
228 Bytes
| { | |
| "bos_token_id": 50256, | |
| "eos_token_id": 50256, | |
| "pad_token_id": 50256, | |
| "max_new_tokens": 80, | |
| "do_sample": true, | |
| "temperature": 0.85, | |
| "top_p": 0.92, | |
| "repetition_penalty": 1.15, | |
| "transformers_version": "4.46.3" | |
| } |