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

Libraries

How to use MiaoshouAI/Florence-2-base-PromptGen with Transformers:

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

pipe = pipeline("image-text-to-text", model="MiaoshouAI/Florence-2-base-PromptGen", trust_remote_code=True)

# Load model directly
from transformers import AutoProcessor, AutoModelForImageTextToText

processor = AutoProcessor.from_pretrained("MiaoshouAI/Florence-2-base-PromptGen", trust_remote_code=True)
model = AutoModelForImageTextToText.from_pretrained("MiaoshouAI/Florence-2-base-PromptGen", trust_remote_code=True)

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use MiaoshouAI/Florence-2-base-PromptGen with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/MiaoshouAI/Florence-2-base-PromptGen

SGLang

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

Docker Model Runner
How to use MiaoshouAI/Florence-2-base-PromptGen with Docker Model Runner:
```
docker model run hf.co/MiaoshouAI/Florence-2-base-PromptGen
```

"cleaned tags"

by seedmanc - opened Aug 20, 2024

Discussion

seedmanc

Aug 20, 2024

•

edited Aug 20, 2024

Wtf is "xrdIno"? And why do the tags contain "ntrcnd" which is "текст" typed in latin keyboard layout? Why does it talk back to me, saying "answering does not require reading text in the image" even though I didn't prompt it to OCR?

Oh right, it's trained on the civitai cesspool where there's zero quality control.

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