Text Generation
Transformers
PyTorch
JAX
English
gpt2
huggingartists
lyrics
lm-head
causal-lm
text-generation-inference
Instructions to use huggingartists/kendrick-lamar with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use huggingartists/kendrick-lamar with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="huggingartists/kendrick-lamar")# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("huggingartists/kendrick-lamar") model = AutoModelForMultimodalLM.from_pretrained("huggingartists/kendrick-lamar") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use huggingartists/kendrick-lamar with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "huggingartists/kendrick-lamar" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "huggingartists/kendrick-lamar", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/huggingartists/kendrick-lamar
- SGLang
How to use huggingartists/kendrick-lamar 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 "huggingartists/kendrick-lamar" \ --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": "huggingartists/kendrick-lamar", "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 "huggingartists/kendrick-lamar" \ --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": "huggingartists/kendrick-lamar", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use huggingartists/kendrick-lamar with Docker Model Runner:
docker model run hf.co/huggingartists/kendrick-lamar
- Xet hash:
- 083fa7672c069fc0c18ee78bece412dd47d64ca1fc3e7b7b8326f99df353b981
- Size of remote file:
- 510 MB
- SHA256:
- 67f487568a255e9e9042f91dd7855b3caf475b0f5a00376c709fb2fd36f143e6
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