Instructions to use microsoft/Florence-2-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use microsoft/Florence-2-large with Transformers:

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

pipe = pipeline("image-text-to-text", model="microsoft/Florence-2-large", trust_remote_code=True)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoProcessor, AutoModelForMultimodalLM

processor = AutoProcessor.from_pretrained("microsoft/Florence-2-large", trust_remote_code=True)
model = AutoModelForMultimodalLM.from_pretrained("microsoft/Florence-2-large", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use microsoft/Florence-2-large with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "microsoft/Florence-2-large"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "microsoft/Florence-2-large",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/microsoft/Florence-2-large

SGLang

How to use microsoft/Florence-2-large 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 "microsoft/Florence-2-large" \
    --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": "microsoft/Florence-2-large",
		"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 "microsoft/Florence-2-large" \
        --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": "microsoft/Florence-2-large",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use microsoft/Florence-2-large with Docker Model Runner:
```
docker model run hf.co/microsoft/Florence-2-large
```

Florence-2-large / processing_florence2.py

Commit History

Aug 13

20:12
Fix AttributeError: tokenizer has no attribute additional_special_tokens⁠

masterofaudio2077

Verified signature
6afac77

Nov 15, 2024

05:07
add_confidence_score (#56)⁠

haipingwu

Verified signature
f0acedb

Aug 21, 2024

05:37
Fix invalid escape sequences (#65)⁠

leoxiaobin +1: jkawamoto

Verified signature
39ddb41

Jul 20, 2024

00:13
update_model_init_fp16 (#53)⁠

leoxiaobin +1: haipingwu

Verified signature
6bf1792

Jul 19, 2024

00:44
update_ocr_postprocess (#52)⁠

leoxiaobin +1: haipingwu

Verified signature
df93020

Jun 26, 2024

07:24
Fix runon lines (#16)⁠

leoxiaobin +1: milekpl

Verified signature
aec3bc5

Jun 15, 2024

01:00
add_model (#1)⁠

leoxiaobin +1: haipingwu

Verified signature
33ee8e1

Commit History

Aug 13

Fix AttributeError: tokenizer has no attribute additional_special_tokens⁠

Nov 15, 2024

add_confidence_score (#56)⁠

Aug 21, 2024

Fix invalid escape sequences (#65)⁠

Jul 20, 2024

update_model_init_fp16 (#53)⁠

Jul 19, 2024

update_ocr_postprocess (#52)⁠

Jun 26, 2024

Fix runon lines (#16)⁠

Jun 15, 2024

add_model (#1)⁠