Instructions to use wvangils/CTRL-Beatles-Lyrics-finetuned-newlyrics with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wvangils/CTRL-Beatles-Lyrics-finetuned-newlyrics with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="wvangils/CTRL-Beatles-Lyrics-finetuned-newlyrics")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("wvangils/CTRL-Beatles-Lyrics-finetuned-newlyrics") model = AutoModelForCausalLM.from_pretrained("wvangils/CTRL-Beatles-Lyrics-finetuned-newlyrics", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use wvangils/CTRL-Beatles-Lyrics-finetuned-newlyrics with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "wvangils/CTRL-Beatles-Lyrics-finetuned-newlyrics" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "wvangils/CTRL-Beatles-Lyrics-finetuned-newlyrics", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/wvangils/CTRL-Beatles-Lyrics-finetuned-newlyrics
- SGLang
How to use wvangils/CTRL-Beatles-Lyrics-finetuned-newlyrics 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 "wvangils/CTRL-Beatles-Lyrics-finetuned-newlyrics" \ --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": "wvangils/CTRL-Beatles-Lyrics-finetuned-newlyrics", "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 "wvangils/CTRL-Beatles-Lyrics-finetuned-newlyrics" \ --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": "wvangils/CTRL-Beatles-Lyrics-finetuned-newlyrics", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use wvangils/CTRL-Beatles-Lyrics-finetuned-newlyrics with Docker Model Runner:
docker model run hf.co/wvangils/CTRL-Beatles-Lyrics-finetuned-newlyrics
Download tokenizer_config.json from wvangils/CTRL-Beatles-Lyrics-finetuned-newlyrics: direct link, hf CLI and curl.
- Browser
- Download file 320 Bytes
-
https://huggingface.co/wvangils/CTRL-Beatles-Lyrics-finetuned-newlyrics/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://wvangils/CTRL-Beatles-Lyrics-finetuned-newlyrics/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/wvangils/CTRL-Beatles-Lyrics-finetuned-newlyrics/resolve/main/tokenizer_config.json
320 Bytes
| {"unk_token": "<unk>", "model_max_length": 256, "special_tokens_map_file": "/root/.cache/huggingface/transformers/17798ce6b7a938460c918134378546ce969a0d31884d01d733251fc25410e092.3766b2880f7f2c1cf6aa2e79dec8b09b08c625bfeb6ae8cfaeaf2f1a1f3ee79d", "name_or_path": "sshleifer/tiny-ctrl", "tokenizer_class": "CTRLTokenizer"} |