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)

# 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
```

Fix two transformers-v5 AttributeErrors in Florence-2 remote code

#122

by masterofaudio2077 - opened 4 days ago

base: refs/heads/main

←

from: refs/pr/122

Discussion Files changed

4 days ago

transformers v5 changed two things this repo's remote code still assumes the old behavior for (see MIGRATION_GUIDE_V5.md):

forced_bos_token_id is no longer auto-set as a config instance attribute ('Modeling > Generate'). Florence2LanguageConfig read self.forced_bos_token_id assuming the old behavior.
additional_special_tokens was renamed to extra_special_tokens. Florence2Processor.__init__ read the old attribute name, raising AttributeError.

Both fixes are minimal and backward compatible with transformers v4. Related: kijai/ComfyUI-Florence2#187, #199, Comfy-Org/ComfyUI#12277, Lightricks/ComfyUI-LTXVideo#394 all hit the symptom of bug 1. #119 also contains fixes for both but bundles them with a full-repo rewrite that corrupts config.json (swaps in Florence-2-base's architecture dimensions), so it's not safe to merge as-is -- this PR is scoped to just these two AttributeErrors. Supersedes #121, which fixed bug 1 alone and later had bug 2 added as a second commit; this PR bundles both from the start instead.

Fix two transformers-v5 AttributeErrors in Florence-2 remote code67061fd4

Fix silently-skipped resize/normalize from None-valued processor kwargs5e92a22c

Fix AttributeError from _supports_sdpa read before language_model existsc13af624

Fix TypeError: EncoderDecoderCache is not subscriptable in prepare_inputs_for_generation9cb81b60

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