Instructions to use SL-AI/GRaPE-Mini with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use SL-AI/GRaPE-Mini with Transformers:

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

pipe = pipeline("text-generation", model="SL-AI/GRaPE-Mini")
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
pipe(text=messages)

# Load model directly
from transformers import AutoProcessor, AutoModelForImageTextToText

processor = AutoProcessor.from_pretrained("SL-AI/GRaPE-Mini")
model = AutoModelForImageTextToText.from_pretrained("SL-AI/GRaPE-Mini")
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
inputs = processor.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use SL-AI/GRaPE-Mini with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "SL-AI/GRaPE-Mini"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "SL-AI/GRaPE-Mini",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/SL-AI/GRaPE-Mini

SGLang

How to use SL-AI/GRaPE-Mini 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 "SL-AI/GRaPE-Mini" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "SL-AI/GRaPE-Mini",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

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 "SL-AI/GRaPE-Mini" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "SL-AI/GRaPE-Mini",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use SL-AI/GRaPE-Mini with Docker Model Runner:
```
docker model run hf.co/SL-AI/GRaPE-Mini
```

Sweaterdog

DedeProGames commited on Mar 29

Commit

afe11c3

1 Parent(s): 65fec46

Update README.md (#2)

Browse files

- Update README.md (00cf3db0673eeec21fb5062b9401df1f648ddcee)

Co-authored-by: DedeProGames <DedeProGames@users.noreply.huggingface.co>

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README.md +3 -0

README.md CHANGED Viewed

@@ -4,6 +4,9 @@ language:
 - en
 pipeline_tag: text-generation
 library_name: transformers
 ---
 ![GRaPE_Logo](https://cdn-uploads.huggingface.co/production/uploads/66960602f0ffd8e3a381106a/XjHkzctrE41e1qqJYeDzN.png)

 - en
 pipeline_tag: text-generation
 library_name: transformers
+datasets:
+- SL-AI/GRaPE-Base-Mix
+- SL-AI/GRaPE-Thinking-Mix
 ---
 ![GRaPE_Logo](https://cdn-uploads.huggingface.co/production/uploads/66960602f0ffd8e3a381106a/XjHkzctrE41e1qqJYeDzN.png)