Instructions to use igorktech/t5-base-lyrics-explainer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use igorktech/t5-base-lyrics-explainer with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="igorktech/t5-base-lyrics-explainer")

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM

tokenizer = AutoTokenizer.from_pretrained("igorktech/t5-base-lyrics-explainer")
model = AutoModelForSeq2SeqLM.from_pretrained("igorktech/t5-base-lyrics-explainer", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use igorktech/t5-base-lyrics-explainer with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "igorktech/t5-base-lyrics-explainer"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "igorktech/t5-base-lyrics-explainer",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/igorktech/t5-base-lyrics-explainer

SGLang

How to use igorktech/t5-base-lyrics-explainer 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 "igorktech/t5-base-lyrics-explainer" \
    --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": "igorktech/t5-base-lyrics-explainer",
		"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 "igorktech/t5-base-lyrics-explainer" \
        --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": "igorktech/t5-base-lyrics-explainer",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use igorktech/t5-base-lyrics-explainer with Docker Model Runner:
```
docker model run hf.co/igorktech/t5-base-lyrics-explainer
```

t5-base-lyrics-explainer

Commit History

Mar 22, 2023

20:17
Adding `safetensors` variant of this model⁠

SFconvertbot

34dfe9f

Mar 21, 2023

17:01
Upload tokenizer

igorktech

6088030
17:01
Upload T5ForConditionalGeneration

igorktech

2c4edf7
17:01
initial commit

igorktech

2bfcf40

Commit History

Mar 22, 2023

Adding `safetensors` variant of this model⁠

Mar 21, 2023

Upload tokenizer

Upload T5ForConditionalGeneration

initial commit