Instructions to use 5dimension/sentinel-universal-tokenizer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use 5dimension/sentinel-universal-tokenizer with Transformers:

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

pipe = pipeline("text-generation", model="5dimension/sentinel-universal-tokenizer")

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("5dimension/sentinel-universal-tokenizer", dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use 5dimension/sentinel-universal-tokenizer with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "5dimension/sentinel-universal-tokenizer"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "5dimension/sentinel-universal-tokenizer",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/5dimension/sentinel-universal-tokenizer

SGLang

How to use 5dimension/sentinel-universal-tokenizer 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 "5dimension/sentinel-universal-tokenizer" \
    --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": "5dimension/sentinel-universal-tokenizer",
		"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 "5dimension/sentinel-universal-tokenizer" \
        --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": "5dimension/sentinel-universal-tokenizer",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use 5dimension/sentinel-universal-tokenizer with Docker Model Runner:
```
docker model run hf.co/5dimension/sentinel-universal-tokenizer
```

sentinel-universal-tokenizer / tokenizer_config.json

5dimension

🦴 Sentinel Universal Tokenizer v1.0 — multimodal tokenizer grounded in Gradient Axiom

c488e22 verified 12 days ago

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	{
	"backend": "tokenizers",
	"bos_token": "<s>",
	"eos_token": "</s>",
	"extra_special_tokens": [
	"<text_start>",
	"<text_end>",
	"<image_start>",
	"<image_end>",
	"<image>",
	"<audio_start>",
	"<audio_end>",
	"<audio>",
	"<video_start>",
	"<video_end>",
	"<video>",
	"<sentinel>",
	"<sentinel_c1>",
	"<sentinel_c2>",
	"<scale_1e>",
	"<translate>",
	"<summarize>",
	"<generate>",
	"<understand>",
	"<caption>",
	"<turn>",
	"<system>",
	"<user>",
	"<assistant>",
	"<code_start>",
	"<code_end>",
	"<math_start>",
	"<math_end>"
	],
	"mask_token": "<mask>",
	"model_max_length": 8192,
	"pad_token": "<pad>",
	"padding_side": "right",
	"tokenizer_class": "TokenizersBackend",
	"truncation_side": "right",
	"unk_token": "<unk>"
	}