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

Libraries

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

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

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

# Load model directly
from transformers import AutoProcessor, AutoModelForImageTextToText

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

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

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

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "microsoft/Florence-2-base"
# 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-base",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

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

SGLang

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

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

Fix incorrect bos_token, eos_token, and pad_token ids in config.json

by Xenova HF Staff - opened Jun 21, 2024

base: refs/heads/main

←

from: refs/pr/6

Discussion Files changed

-3

Files changed (1) hide show

config.json +3 -3

config.json CHANGED Viewed

@@ -7,11 +7,11 @@
     "AutoConfig": "configuration_florence2.Florence2Config",
     "AutoModelForCausalLM": "modeling_florence2.Florence2ForConditionalGeneration"
   },
-  "bos_token_id": 2,
-  "eos_token_id": 1,
   "ignore_index": -100,
   "model_type": "florence2",
-  "pad_token_id": 0,
   "projection_dim": 768,
   "text_config": {
       "vocab_size": 51289,

     "AutoConfig": "configuration_florence2.Florence2Config",
     "AutoModelForCausalLM": "modeling_florence2.Florence2ForConditionalGeneration"
   },
+  "bos_token_id": 0,
+  "eos_token_id": 2,
   "ignore_index": -100,
   "model_type": "florence2",
+  "pad_token_id": 1,
   "projection_dim": 768,
   "text_config": {
       "vocab_size": 51289,