Image-Text-to-Text
Transformers
PyTorch
Safetensors
florence2
GUI
VLM
Agent
GUI-Grounding
custom_code
Instructions to use HongxinLi/GoClick-Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HongxinLi/GoClick-Base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="HongxinLi/GoClick-Base", trust_remote_code=True)# Load model directly from transformers import AutoProcessor, AutoModelForImageTextToText processor = AutoProcessor.from_pretrained("HongxinLi/GoClick-Base", trust_remote_code=True) model = AutoModelForImageTextToText.from_pretrained("HongxinLi/GoClick-Base", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use HongxinLi/GoClick-Base with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "HongxinLi/GoClick-Base" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "HongxinLi/GoClick-Base", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/HongxinLi/GoClick-Base
- SGLang
How to use HongxinLi/GoClick-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 "HongxinLi/GoClick-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": "HongxinLi/GoClick-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 "HongxinLi/GoClick-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": "HongxinLi/GoClick-Base", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use HongxinLi/GoClick-Base with Docker Model Runner:
docker model run hf.co/HongxinLi/GoClick-Base
| { | |
| "_name_or_path": "florence2", | |
| "architectures": [ | |
| "Florence2ForConditionalGeneration" | |
| ], | |
| "auto_map": { | |
| "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, | |
| "activation_dropout": 0.1, | |
| "activation_function": "gelu", | |
| "add_bias_logits": false, | |
| "add_final_layer_norm": false, | |
| "attention_dropout": 0.1, | |
| "bos_token_id": 0, | |
| "classif_dropout": 0.1, | |
| "classifier_dropout": 0.0, | |
| "d_model": 768, | |
| "decoder_attention_heads": 12, | |
| "decoder_ffn_dim": 3072, | |
| "decoder_layerdrop": 0.0, | |
| "decoder_layers": 6, | |
| "decoder_start_token_id": 2, | |
| "dropout": 0.1, | |
| "early_stopping": true, | |
| "encoder_attention_heads": 12, | |
| "encoder_ffn_dim": 3072, | |
| "encoder_layerdrop": 0.0, | |
| "encoder_layers": 6, | |
| "eos_token_id": 2, | |
| "forced_eos_token_id": 2, | |
| "forced_bos_token_id": 0, | |
| "gradient_checkpointing": false, | |
| "init_std": 0.02, | |
| "is_encoder_decoder": true, | |
| "label2id": { | |
| "LABEL_0": 0, | |
| "LABEL_1": 1, | |
| "LABEL_2": 2 | |
| }, | |
| "max_position_embeddings": 1024, | |
| "no_repeat_ngram_size": 3, | |
| "normalize_before": false, | |
| "num_hidden_layers": 6, | |
| "pad_token_id": 1, | |
| "scale_embedding": false, | |
| "num_beams": 3 | |
| }, | |
| "vision_config": { | |
| "model_type": "davit", | |
| "drop_path_rate": 0.1, | |
| "patch_size": [7, 3, 3, 3], | |
| "patch_stride": [4, 2, 2, 2], | |
| "patch_padding": [3, 1, 1, 1], | |
| "patch_prenorm": [false, true, true, true], | |
| "enable_checkpoint": false, | |
| "dim_embed": [128, 256, 512, 1024], | |
| "num_heads": [4, 8, 16, 32], | |
| "num_groups": [4, 8, 16, 32], | |
| "depths": [1, 1, 9, 1], | |
| "window_size": 12, | |
| "projection_dim": 768, | |
| "visual_temporal_embedding": { | |
| "type": "COSINE", | |
| "max_temporal_embeddings": 100 | |
| }, | |
| "image_pos_embed": { | |
| "type": "learned_abs_2d", | |
| "max_pos_embeddings": 50 | |
| }, | |
| "image_feature_source": ["spatial_avg_pool", "temporal_avg_pool"] | |
| }, | |
| "vocab_size": 51289, | |
| "torch_dtype": "float16", | |
| "transformers_version": "4.41.0.dev0", | |
| "is_encoder_decoder": true | |
| } |