Instructions to use notlikejoe/tiny-random-MiniCPM-o-2_6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use notlikejoe/tiny-random-MiniCPM-o-2_6 with Transformers:

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

pipe = pipeline("text-generation", model="notlikejoe/tiny-random-MiniCPM-o-2_6", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("notlikejoe/tiny-random-MiniCPM-o-2_6", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use notlikejoe/tiny-random-MiniCPM-o-2_6 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "notlikejoe/tiny-random-MiniCPM-o-2_6"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "notlikejoe/tiny-random-MiniCPM-o-2_6",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/notlikejoe/tiny-random-MiniCPM-o-2_6

SGLang

How to use notlikejoe/tiny-random-MiniCPM-o-2_6 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 "notlikejoe/tiny-random-MiniCPM-o-2_6" \
    --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": "notlikejoe/tiny-random-MiniCPM-o-2_6",
		"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 "notlikejoe/tiny-random-MiniCPM-o-2_6" \
        --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": "notlikejoe/tiny-random-MiniCPM-o-2_6",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use notlikejoe/tiny-random-MiniCPM-o-2_6 with Docker Model Runner:
```
docker model run hf.co/notlikejoe/tiny-random-MiniCPM-o-2_6
```

tiny-random-MiniCPM-o-2_6 / special_tokens_map.json

notlikejoe

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	{
	"additional_special_tokens": [
	"<image>",
	"</image>",
	"<ref>",
	"</ref>",
	"<box>",
	"</box>",
	"<quad>",
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	"<point>",
	"</point>",
	"<slice>",
	"</slice>",
	"<image_id>",
	"</image_id>",
	"<unit>",
	"</unit>",
	"<asr>",
	"</asr>",
	"<query>",
	"</query>",
	"<\|audio_start\|>",
	"<\|audio\|>",
	"<\|audio_end\|>",
	"<\|spk_bos\|>",
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	"<\|spk_eos\|>",
	"<\|tts_bos\|>",
	"<\|tts_eos\|>",
	"<\|listen\|>",
	"<\|speak\|>",
	"<\|interrupt\|>",
	"<\|vad_start\|>",
	"<\|vad_end\|>",
	"<reserved_43>",
	"<reserved_53>"
	],
	"bos_token": {
	"content": "<\|im_start\|>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false
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	"eos_token": {
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	"unk_token": {
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	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false
	}
	}