Instructions to use SmartPy/handwritten-text-recognition with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use SmartPy/handwritten-text-recognition with Transformers:

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

pipe = pipeline("image-text-to-text", model="SmartPy/handwritten-text-recognition")

# Load model directly
from transformers import AutoTokenizer, AutoModelForImageTextToText

tokenizer = AutoTokenizer.from_pretrained("SmartPy/handwritten-text-recognition")
model = AutoModelForImageTextToText.from_pretrained("SmartPy/handwritten-text-recognition")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use SmartPy/handwritten-text-recognition with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/SmartPy/handwritten-text-recognition

SGLang

How to use SmartPy/handwritten-text-recognition 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 "SmartPy/handwritten-text-recognition" \
    --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": "SmartPy/handwritten-text-recognition",
		"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 "SmartPy/handwritten-text-recognition" \
        --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": "SmartPy/handwritten-text-recognition",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use SmartPy/handwritten-text-recognition with Docker Model Runner:
```
docker model run hf.co/SmartPy/handwritten-text-recognition
```

handwritten-text-recognition / tokenizer_config.json

SmartPy

Training in progress step 566

5ac4cff over 3 years ago

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347 Bytes

	{
	"cls_token": "[CLS]",
	"do_lower_case": false,
	"mask_token": "[MASK]",
	"model_max_length": 512,
	"name_or_path": "bert-base-cased",
	"pad_token": "[PAD]",
	"sep_token": "[SEP]",
	"special_tokens_map_file": null,
	"strip_accents": null,
	"tokenize_chinese_chars": true,
	"tokenizer_class": "BertTokenizer",
	"unk_token": "[UNK]"
	}