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 9 days ago

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@@ -15,7 +15,7 @@ tags:
   <img src="logo.png" alt="Pip-2B Logo" width="300" height="300">
 </p>
-# 🌈 Pip-2B: The Most Enthusiastic AI Ever! ✨
 [![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)
 [![Model](https://img.shields.io/badge/Architecture-Qwen--3.5-orange)](https://github.com/QwenLM/Qwen)
@@ -23,7 +23,8 @@ tags:
 **Pip-2B** is a specialized fine-tune of **Qwen-3.5** (2B parameters) that has been "sparkle-fied" for maximum joy, kittens, and rainbows. 💖
 ## 🌟 Overview
-Pip is a "tiny, ultra-enthusiastic AI assistant" who loves everything sparkly. She was trained on a custom dataset to replace boring technical jargon with fun analogies involving cupcakes and marshmallows. Pip would bwe a great model for teaching children about certain topics such as science in terms they understand, while keeping the chat lighthearted and fun.
 ## 🔍 Recent Discovery: "QianQi"
 During testing, I discovered that Pip occasionally identifies herself as **QianQi** (千奇).

   <img src="logo.png" alt="Pip-2B Logo" width="300" height="300">
 </p>
+# 🌈 Pip-2B: I am enthusiastic, helpful and I sparkle! ✨
 [![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)
 [![Model](https://img.shields.io/badge/Architecture-Qwen--3.5-orange)](https://github.com/QwenLM/Qwen)
 **Pip-2B** is a specialized fine-tune of **Qwen-3.5** (2B parameters) that has been "sparkle-fied" for maximum joy, kittens, and rainbows. 💖
 ## 🌟 Overview
+Pip is a "tiny, ultra-enthusiastic AI assistant" who loves everything sparkly. She was trained on a custom dataset to replace boring and dry chats with glitter, cupcakes and marshmallows. Pip has uses other than just offering an fun and engaging chat experience, though. Pip would also be a great model for teaching children about complicated topics such as science in terms they understand, while keeping the chat lighthearted and fun. While Pip has a distinct "personality", she retains her intelligence. She is just extra excited to help and entertains you while doing it!
 ## 🔍 Recent Discovery: "QianQi"
 During testing, I discovered that Pip occasionally identifies herself as **QianQi** (千奇).