Instructions to use htrnguyen/GOT_Vietnamese_custom with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use htrnguyen/GOT_Vietnamese_custom with Transformers:

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

pipe = pipeline("image-text-to-text", model="htrnguyen/GOT_Vietnamese_custom", trust_remote_code=True)

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("htrnguyen/GOT_Vietnamese_custom", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use htrnguyen/GOT_Vietnamese_custom with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/htrnguyen/GOT_Vietnamese_custom

SGLang

How to use htrnguyen/GOT_Vietnamese_custom 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 "htrnguyen/GOT_Vietnamese_custom" \
    --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": "htrnguyen/GOT_Vietnamese_custom",
		"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 "htrnguyen/GOT_Vietnamese_custom" \
        --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": "htrnguyen/GOT_Vietnamese_custom",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use htrnguyen/GOT_Vietnamese_custom with Docker Model Runner:
```
docker model run hf.co/htrnguyen/GOT_Vietnamese_custom
```

Usage

Inference using Huggingface transformers on NVIDIA GPUs. Requirements tested on python 3.10：

torch==2.0.1
torchvision==0.15.2
transformers==4.37.2
tiktoken==0.6.0
verovio==4.3.1
accelerate==0.28.0

from transformers import AutoModel, AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained('htrnguyen/GOT_Vietnamese_custom', trust_remote_code=True)
model = AutoModel.from_pretrained('htrnguyen/GOT_Vietnamese_custom', trust_remote_code=True, low_cpu_mem_usage=True, device_map='cuda', use_safetensors=True, pad_token_id=tokenizer.eos_token_id)
model = model.eval().cuda()
# input your test image
image_file = 'xxx.jpg'
# plain texts OCR
res = model.chat(tokenizer, image_file, ocr_type='ocr')
print(res)

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Safetensors

Model size

0.6B params

Tensor type

BF16

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Image-Text-to-Text

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