Instructions to use PinkPixel/Pip-2B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use PinkPixel/Pip-2B with Transformers:

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

pipe = pipeline("image-text-to-text", model="PinkPixel/Pip-2B")
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("PinkPixel/Pip-2B")
model = AutoModelForImageTextToText.from_pretrained("PinkPixel/Pip-2B")
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 PinkPixel/Pip-2B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "PinkPixel/Pip-2B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "PinkPixel/Pip-2B",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Use Docker

docker model run hf.co/PinkPixel/Pip-2B

SGLang

How to use PinkPixel/Pip-2B 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 "PinkPixel/Pip-2B" \
    --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": "PinkPixel/Pip-2B",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

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 "PinkPixel/Pip-2B" \
        --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": "PinkPixel/Pip-2B",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Docker Model Runner
How to use PinkPixel/Pip-2B with Docker Model Runner:
```
docker model run hf.co/PinkPixel/Pip-2B
```

sizzlebop commited on 20 days ago

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@@ -62,7 +62,7 @@ Here is a sneak peek at what it's like to talk to Pip! 🍭
 **Pip:** "Bedtime story time is a sQUEEE! of happy energy! *Twirls around.* Yes! It's a story of a big pink star that floats in the sky and does magic with its tail! It has a voice that says 'YAY! Sleepy-time is best!' It tells us to close our eyes and count the pink flowers on the garden. And I see its tiny feet that leave a giant pink print! Sleep well, Marshmallow! Pip is your best storyteller!" 😴💫
 ## 💎 Dataset
-The model was trained on the `dataset/pip.jsonl` file, which contains 1000+ examples of Pip's unique communication style.
 ## 🛠️ Installation
 ```bash

 **Pip:** "Bedtime story time is a sQUEEE! of happy energy! *Twirls around.* Yes! It's a story of a big pink star that floats in the sky and does magic with its tail! It has a voice that says 'YAY! Sleepy-time is best!' It tells us to close our eyes and count the pink flowers on the garden. And I see its tiny feet that leave a giant pink print! Sleep well, Marshmallow! Pip is your best storyteller!" 😴💫
 ## 💎 Dataset
+The model was trained on a custom "Pip" dataset created by me which defines her personality and communication style.
 ## 🛠️ Installation
 ```bash