Instructions to use danelcsb/Florence-2-FT-cppe-5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use danelcsb/Florence-2-FT-cppe-5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="danelcsb/Florence-2-FT-cppe-5", trust_remote_code=True)# Load model directly from transformers import AutoProcessor, AutoModelForImageTextToText processor = AutoProcessor.from_pretrained("danelcsb/Florence-2-FT-cppe-5", trust_remote_code=True) model = AutoModelForImageTextToText.from_pretrained("danelcsb/Florence-2-FT-cppe-5", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use danelcsb/Florence-2-FT-cppe-5 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "danelcsb/Florence-2-FT-cppe-5" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "danelcsb/Florence-2-FT-cppe-5", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/danelcsb/Florence-2-FT-cppe-5
- SGLang
How to use danelcsb/Florence-2-FT-cppe-5 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 "danelcsb/Florence-2-FT-cppe-5" \ --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": "danelcsb/Florence-2-FT-cppe-5", "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 "danelcsb/Florence-2-FT-cppe-5" \ --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": "danelcsb/Florence-2-FT-cppe-5", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use danelcsb/Florence-2-FT-cppe-5 with Docker Model Runner:
docker model run hf.co/danelcsb/Florence-2-FT-cppe-5
Upload processor
Browse files- preprocessor_config.json +1 -1
- tokenizer_config.json +0 -3
preprocessor_config.json
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"input_data_format"
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],
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"auto_map": {
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"AutoProcessor": "processing_florence2.Florence2Processor"
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},
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"crop_size": {
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"height": 768,
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"input_data_format"
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],
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"auto_map": {
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"AutoProcessor": "microsoft/Florence-2-large-ft--processing_florence2.Florence2Processor"
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},
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"crop_size": {
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"height": 768,
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tokenizer_config.json
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"</poly>",
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"<and>"
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],
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"auto_map": {
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"AutoProcessor": "processing_florence2.Florence2Processor"
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},
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"bos_token": "<s>",
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"clean_up_tokenization_spaces": true,
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"cls_token": "<s>",
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"</poly>",
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"<and>"
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],
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"bos_token": "<s>",
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"clean_up_tokenization_spaces": true,
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"cls_token": "<s>",
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