Instructions to use systemk-ai/glm-ocr-receipt-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use systemk-ai/glm-ocr-receipt-lora with PEFT:

from peft import PeftModel
from transformers import AutoModelForCausalLM

base_model = AutoModelForCausalLM.from_pretrained("zai-org/GLM-OCR")
model = PeftModel.from_pretrained(base_model, "systemk-ai/glm-ocr-receipt-lora")

Transformers

How to use systemk-ai/glm-ocr-receipt-lora with Transformers:

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

pipe = pipeline("text-generation", model="systemk-ai/glm-ocr-receipt-lora")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("systemk-ai/glm-ocr-receipt-lora", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use systemk-ai/glm-ocr-receipt-lora with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "systemk-ai/glm-ocr-receipt-lora"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "systemk-ai/glm-ocr-receipt-lora",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/systemk-ai/glm-ocr-receipt-lora

SGLang

How to use systemk-ai/glm-ocr-receipt-lora 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 "systemk-ai/glm-ocr-receipt-lora" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "systemk-ai/glm-ocr-receipt-lora",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

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 "systemk-ai/glm-ocr-receipt-lora" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "systemk-ai/glm-ocr-receipt-lora",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Unsloth Desktop
Docker Model Runner
How to use systemk-ai/glm-ocr-receipt-lora with Docker Model Runner:
```
docker model run hf.co/systemk-ai/glm-ocr-receipt-lora
```

You need to agree to share your Hugging Face information to access this model

This repository is publicly accessible, but you have to accept the conditions to access its files and content.

Gated model

You can list files but not access them

Preview of files found in this repository

You need to agree to share your Hugging Face information to access this model

Gated model You can list files but not access them

Gated model

You can list files but not access them