Instructions to use EvanOLeary/laguna-xs2-densify-smoke with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use EvanOLeary/laguna-xs2-densify-smoke with Transformers:

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

pipe = pipeline("text-generation", model="EvanOLeary/laguna-xs2-densify-smoke")

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("EvanOLeary/laguna-xs2-densify-smoke", dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use EvanOLeary/laguna-xs2-densify-smoke with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "EvanOLeary/laguna-xs2-densify-smoke"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "EvanOLeary/laguna-xs2-densify-smoke",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/EvanOLeary/laguna-xs2-densify-smoke

SGLang

How to use EvanOLeary/laguna-xs2-densify-smoke 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 "EvanOLeary/laguna-xs2-densify-smoke" \
    --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": "EvanOLeary/laguna-xs2-densify-smoke",
		"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 "EvanOLeary/laguna-xs2-densify-smoke" \
        --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": "EvanOLeary/laguna-xs2-densify-smoke",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use EvanOLeary/laguna-xs2-densify-smoke with Docker Model Runner:
```
docker model run hf.co/EvanOLeary/laguna-xs2-densify-smoke
```

Add metadata and paper/code links

by nielsr HF Staff - opened 30 days ago

base: refs/heads/main

←

from: refs/pr/1

Discussion Files changed

-1

nielsr

30 days ago

Hi, I'm Niels from the community science team at Hugging Face.

This PR improves the model card by adding relevant metadata (license, library name, and pipeline tag) and linking the repository to the original research paper and official code implementation. This ensures the model is properly indexed and discoverable on the Hub.

Add metadata and paper/code linksc9a84200

EvanOLeary changed pull request status to merged 29 days ago

EvanOLeary

Owner 29 days ago

Thanks Niels for your contribution! I'll keep this in mind for next time :)

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