Instructions to use jinhybr/UDP-RVL-CDIP with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jinhybr/UDP-RVL-CDIP with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="jinhybr/UDP-RVL-CDIP")# Load model directly from transformers import AutoProcessor, AutoModelForImageTextToText processor = AutoProcessor.from_pretrained("jinhybr/UDP-RVL-CDIP") model = AutoModelForImageTextToText.from_pretrained("jinhybr/UDP-RVL-CDIP") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use jinhybr/UDP-RVL-CDIP with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "jinhybr/UDP-RVL-CDIP" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "jinhybr/UDP-RVL-CDIP", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/jinhybr/UDP-RVL-CDIP
- SGLang
How to use jinhybr/UDP-RVL-CDIP 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 "jinhybr/UDP-RVL-CDIP" \ --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": "jinhybr/UDP-RVL-CDIP", "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 "jinhybr/UDP-RVL-CDIP" \ --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": "jinhybr/UDP-RVL-CDIP", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use jinhybr/UDP-RVL-CDIP with Docker Model Runner:
docker model run hf.co/jinhybr/UDP-RVL-CDIP
| { | |
| "_name_or_path": "microsoft/udop-large", | |
| "architectures": [ | |
| "UdopForConditionalGeneration" | |
| ], | |
| "d_ff": 4096, | |
| "d_kv": 64, | |
| "d_model": 1024, | |
| "decoder_start_token_id": 0, | |
| "dense_act_fn": "relu", | |
| "dropout_rate": 0.1, | |
| "eos_token_id": 1, | |
| "feed_forward_proj": "relu", | |
| "image_size": 224, | |
| "initializer_factor": 1.0, | |
| "is_encoder_decoder": true, | |
| "is_gated_act": false, | |
| "layer_norm_epsilon": 1e-06, | |
| "max_2d_position_embeddings": 1024, | |
| "model_type": "udop", | |
| "num_channels": 3, | |
| "num_decoder_layers": 24, | |
| "num_heads": 16, | |
| "num_layers": 24, | |
| "pad_token_id": 0, | |
| "patch_size": 16, | |
| "relative_attention_max_distance": 128, | |
| "relative_attention_num_buckets": 32, | |
| "relative_bias_args": [ | |
| { | |
| "type": "1d" | |
| }, | |
| { | |
| "type": "horizontal" | |
| }, | |
| { | |
| "type": "vertical" | |
| } | |
| ], | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.39.0.dev0", | |
| "use_cache": true, | |
| "vocab_size": 33201 | |
| } | |