Instructions to use Shanav12/swift_lyrics_gen3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Shanav12/swift_lyrics_gen3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Shanav12/swift_lyrics_gen3")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Shanav12/swift_lyrics_gen3") model = AutoModelForCausalLM.from_pretrained("Shanav12/swift_lyrics_gen3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Shanav12/swift_lyrics_gen3 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Shanav12/swift_lyrics_gen3" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Shanav12/swift_lyrics_gen3", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Shanav12/swift_lyrics_gen3
- SGLang
How to use Shanav12/swift_lyrics_gen3 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 "Shanav12/swift_lyrics_gen3" \ --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": "Shanav12/swift_lyrics_gen3", "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 "Shanav12/swift_lyrics_gen3" \ --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": "Shanav12/swift_lyrics_gen3", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Shanav12/swift_lyrics_gen3 with Docker Model Runner:
docker model run hf.co/Shanav12/swift_lyrics_gen3
- Xet hash:
- ee08786a3297b24efb7fb213f8068d7cd2eccd99068ca3cdc4348ec97c77cd2d
- Size of remote file:
- 3.9 kB
- SHA256:
- ffab322a4a92c34cd346e84cf165e1b7474a3a3728844c8f1885b73e8d72de0b
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