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

File size: 1,619 Bytes

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  "version": "json-tokenizer-v1",
  "bpe_vocab_size": 4096,
  "max_key_vocab": 512,
  "min_key_freq": 2,
  "bpe_min_freq": 2,
  "key_vocab": {
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    "app": 60,
    "metadata": 61,
    "labels": 62,
    "spec": 63,
    "cpu": 64,
    "memory": 65,
    "httpGet": 66,
    "port": 67,
    "initialDelaySeconds": 68,
    "periodSeconds": 69,
    "apiVersion": 70,
    "kind": 71,
    "namespace": 72,
    "version": 73,
    "tier": 74,
    "annotations": 75,
    "deployment.kubernetes.io/revision": 76,
    "replicas": 77,
    "selector": 78,
    "matchLabels": 79,
    "template": 80,
    "containers": 81,
    "image": 82,
    "ports": 83,
    "containerPort": 84,
    "protocol": 85,
    "resources": 86,
    "requests": 87,
    "limits": 88,
    "env": 89,
    "livenessProbe": 90,
    "readinessProbe": 91,
    "imagePullSecrets": 92,
    "from": 93,
    "contributor": 94,
    "chat_format": 95,
    "conversations": 96
  },
  "key_offset": 32,
  "bpe_offset": 97
}