Instructions to use drooryck/multilingual-macaroni-models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use drooryck/multilingual-macaroni-models with Transformers:

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

pipe = pipeline("text-generation", model="drooryck/multilingual-macaroni-models")

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("drooryck/multilingual-macaroni-models", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use drooryck/multilingual-macaroni-models with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/drooryck/multilingual-macaroni-models

SGLang

How to use drooryck/multilingual-macaroni-models 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 "drooryck/multilingual-macaroni-models" \
    --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": "drooryck/multilingual-macaroni-models",
		"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 "drooryck/multilingual-macaroni-models" \
        --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": "drooryck/multilingual-macaroni-models",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use drooryck/multilingual-macaroni-models with Docker Model Runner:
```
docker model run hf.co/drooryck/multilingual-macaroni-models
```

Add pipeline tag, link to paper and code

by nielsr HF Staff - opened 15 days ago

base: refs/heads/main

←

from: refs/pr/1

Discussion Files changed

+15

-4

nielsr

15 days ago

This PR adds the missing pipeline_tag (text-generation) to the YAML metadata for better discoverability on the Hub. It also adds links to the paper page and the GitHub repository in the model card content.

Add pipeline tag, link to paper and code26c44d42

drooryck changed pull request status to merged 14 days ago

drooryck

Owner 14 days ago

Thank you!

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