Image-Text-to-Text
Transformers
Safetensors
uhr_bat
text-generation
vision-language
remote-sensing
ultra-high-resolution
query-guided-token-compression
qwen2
longva
uhr-bat
conversational
custom_code
Instructions to use FelixKAI/UHR-BAT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FelixKAI/UHR-BAT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="FelixKAI/UHR-BAT", trust_remote_code=True) messages = [ { "role": "user", "content": [ {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"}, {"type": "text", "text": "What animal is on the candy?"} ] }, ] pipe(text=messages)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("FelixKAI/UHR-BAT", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use FelixKAI/UHR-BAT with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "FelixKAI/UHR-BAT" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "FelixKAI/UHR-BAT", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'Use Docker
docker model run hf.co/FelixKAI/UHR-BAT
- SGLang
How to use FelixKAI/UHR-BAT 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 "FelixKAI/UHR-BAT" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "FelixKAI/UHR-BAT", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'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 "FelixKAI/UHR-BAT" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "FelixKAI/UHR-BAT", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }' - Docker Model Runner
How to use FelixKAI/UHR-BAT with Docker Model Runner:
docker model run hf.co/FelixKAI/UHR-BAT
File size: 2,094 Bytes
6b408dc | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 | {
"_name_or_path": "FelixKAI/UHR-BAT",
"architectures": [
"UHRBATForCausalLM"
],
"attention_dropout": 0.0,
"bos_token_id": 151643,
"debug_print_token_counts": false,
"enable_scale_pos_residual": true,
"eos_token_id": 151645,
"hidden_act": "silu",
"hidden_size": 3584,
"image_aspect_ratio": "pad",
"image_crop_resolution": null,
"image_grid_pinpoints": null,
"image_split_resolution": null,
"initializer_range": 0.02,
"intermediate_size": 18944,
"max_position_embeddings": 224000,
"max_window_layers": 28,
"mm_hidden_size": 1024,
"mm_patch_merge_type": "unires",
"mm_projector_lr": null,
"mm_projector_type": "mlp2x_gelu",
"mm_resampler_type": null,
"mm_spatial_pool_mode": "average",
"mm_spatial_pool_stride": 2,
"mm_tunable_parts": "mm_mlp_adapter,mm_language_model,scale_residuals",
"mm_use_im_patch_token": false,
"mm_use_im_start_end": false,
"mm_vision_select_feature": "patch",
"mm_vision_select_layer": -2,
"mm_vision_tower": "openai/clip-vit-large-patch14-336",
"mm_vision_tower_lr": null,
"model_type": "uhr_bat",
"multiscale_target_sizes": [
672,
1344,
2688,
4032
],
"num_attention_heads": 28,
"num_hidden_layers": 28,
"num_key_value_heads": 4,
"pos_skipping_range": 4096,
"rms_norm_eps": 1e-06,
"rope_scaling": null,
"rope_theta": 1000000000.0,
"sam_checkpoint_path": null,
"sam_keep_ratio": null,
"sam_model_type": "vit_h",
"sam_prune_ratio": 0.9,
"sam_prune_target": 0,
"scale_residual_base": 64,
"sliding_window": null,
"tie_word_embeddings": false,
"tokenizer_model_max_length": 20000,
"tokenizer_padding_side": "right",
"torch_dtype": "bfloat16",
"transformers_version": "4.43.4",
"use_cache": true,
"use_mm_proj": true,
"use_pos_skipping": false,
"use_sliding_window": false,
"vision_tower_pretrained": null,
"vocab_size": 152064,
"auto_map": {
"AutoConfig": "configuration_uhr_bat.UHRBATConfig",
"AutoModelForCausalLM": "modeling_uhr_bat.UHRBATForCausalLM"
},
"library_name": "transformers",
"trust_remote_code": true
}
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