Instructions to use anthonym21/json-tokenizer-structured with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use anthonym21/json-tokenizer-structured with Transformers:

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

pipe = pipeline("text-generation", model="anthonym21/json-tokenizer-structured")

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("anthonym21/json-tokenizer-structured", dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use anthonym21/json-tokenizer-structured with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "anthonym21/json-tokenizer-structured"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "anthonym21/json-tokenizer-structured",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/anthonym21/json-tokenizer-structured

SGLang

How to use anthonym21/json-tokenizer-structured 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 "anthonym21/json-tokenizer-structured" \
    --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": "anthonym21/json-tokenizer-structured",
		"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 "anthonym21/json-tokenizer-structured" \
        --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": "anthonym21/json-tokenizer-structured",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use anthonym21/json-tokenizer-structured with Docker Model Runner:
```
docker model run hf.co/anthonym21/json-tokenizer-structured
```

json-tokenizer-structured / json_tokenizer /__init__.py

anthonym21

Upload json_tokenizer/__init__.py with huggingface_hub

d54e053 verified 3 months ago

raw

history blame contribute delete

849 Bytes

	"""
	json_tokenizer — A tokenizer optimized for JSON structures.

	Architecture:
	- Structural tokens: single-token representations for JSON grammar ({, }, [, ], :, ,)
	- Key tokens: deduplicated key vocabulary with Key() wrapper
	- Value BPE: byte-pair encoding trained on JSON string/number values
	- Type tokens: explicit type markers for faithful roundtrip encoding

	Delivers 5-15% fewer tokens than cl100k_base on schema-repetitive JSON
	with a 90x smaller vocabulary, and lossless roundtrip fidelity.
	"""

	from json_tokenizer.tokenizer import JSONTokenizer
	from json_tokenizer.bpe import BPETrainer

	__version__ = "0.2.0"
	__all__ = ["JSONTokenizer", "BPETrainer"]

	try:
	from json_tokenizer.hf_compat import JSONPreTrainedTokenizer
	__all__.append("JSONPreTrainedTokenizer")
	except ImportError:
	pass # transformers not installed