Instructions to use yasserrmd/smoothie-diffusion-qqp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use yasserrmd/smoothie-diffusion-qqp with Transformers:

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

pipe = pipeline("text-generation", model="yasserrmd/smoothie-diffusion-qqp")

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("yasserrmd/smoothie-diffusion-qqp", dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use yasserrmd/smoothie-diffusion-qqp with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/yasserrmd/smoothie-diffusion-qqp

SGLang

How to use yasserrmd/smoothie-diffusion-qqp 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 "yasserrmd/smoothie-diffusion-qqp" \
    --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": "yasserrmd/smoothie-diffusion-qqp",
		"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 "yasserrmd/smoothie-diffusion-qqp" \
        --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": "yasserrmd/smoothie-diffusion-qqp",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use yasserrmd/smoothie-diffusion-qqp with Docker Model Runner:
```
docker model run hf.co/yasserrmd/smoothie-diffusion-qqp
```

Improve model card: add metadata and links to paper/code

by nielsr HF Staff - opened May 18

base: refs/heads/main

←

from: refs/pr/1

Discussion Files changed

+13

-9

nielsr

May 18

Hi, I'm Niels from the Hugging Face community science team. I've improved the model card for this repository by:

Adding the transformers library name to enable the code snippet feature and "Use in Transformers" button.
Adding the text-generation pipeline tag to improve discoverability.
Adding direct links to the paper and the official GitHub repository.

These changes help users discover the model more easily and provide better documentation for researchers.

Improve model card: add metadata and links to paper/code37e1471f

yasserrmd changed pull request status to merged Jun 1

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