Instructions to use impactframes/GOT-OCR2_0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use impactframes/GOT-OCR2_0 with Transformers:

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

pipe = pipeline("image-text-to-text", model="impactframes/GOT-OCR2_0", trust_remote_code=True)

# Load model directly
from transformers import AutoProcessor, AutoModelForCausalLM

processor = AutoProcessor.from_pretrained("impactframes/GOT-OCR2_0", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("impactframes/GOT-OCR2_0", trust_remote_code=True)

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use impactframes/GOT-OCR2_0 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "impactframes/GOT-OCR2_0"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "impactframes/GOT-OCR2_0",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/impactframes/GOT-OCR2_0

SGLang

How to use impactframes/GOT-OCR2_0 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 "impactframes/GOT-OCR2_0" \
    --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": "impactframes/GOT-OCR2_0",
		"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 "impactframes/GOT-OCR2_0" \
        --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": "impactframes/GOT-OCR2_0",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use impactframes/GOT-OCR2_0 with Docker Model Runner:
```
docker model run hf.co/impactframes/GOT-OCR2_0
```

impactframes commited on Oct 30, 2024

Commit

a7adbf5

verified ·

1 Parent(s): de46c62

Update config.json

Browse files

Files changed (1) hide show

config.json +3 -3

config.json CHANGED Viewed

@@ -1,11 +1,11 @@
 {
   "_name_or_path": "ucaslcl/GOT-OCR2_0",
   "architectures": [
-  "GOTQwenForCausalLM"
   ],
   "auto_map": {
-    "AutoConfig": "modeling_GOT.GOTConfig",
-    "AutoModel": "modeling_GOT.GOTQwenForCausalLM"
   },
   "attention_dropout": 0.0,
   "bos_token_id": 151643,

 {
   "_name_or_path": "ucaslcl/GOT-OCR2_0",
   "architectures": [
+  "QwenForCausalLM"
   ],
   "auto_map": {
+    "AutoConfig": "Config",
+    "AutoModel": "QwenForCausalLM"
   },
   "attention_dropout": 0.0,
   "bos_token_id": 151643,