Image-Text-to-Text
Transformers
Safetensors
PyTorch
English
qwen2_5_vl
multimodal
action
agent
conversational
Eval Results
text-generation-inference
Instructions to use Hcompany/Holo1.5-3B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Hcompany/Holo1.5-3B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="Hcompany/Holo1.5-3B") 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)# Load model directly from transformers import AutoProcessor, AutoModelForImageTextToText processor = AutoProcessor.from_pretrained("Hcompany/Holo1.5-3B") model = AutoModelForImageTextToText.from_pretrained("Hcompany/Holo1.5-3B") 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?"} ] }, ] inputs = processor.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use Hcompany/Holo1.5-3B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Hcompany/Holo1.5-3B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Hcompany/Holo1.5-3B", "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/Hcompany/Holo1.5-3B
- SGLang
How to use Hcompany/Holo1.5-3B 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 "Hcompany/Holo1.5-3B" \ --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": "Hcompany/Holo1.5-3B", "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 "Hcompany/Holo1.5-3B" \ --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": "Hcompany/Holo1.5-3B", "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 Hcompany/Holo1.5-3B with Docker Model Runner:
docker model run hf.co/Hcompany/Holo1.5-3B
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id: likaixin/ScreenSpot-Pro
task_id: overall
value: 51.5
source:
url: https://gui-agent.github.io/grounding-leaderboard/
name: ScreenSpot-Pro Leaderboard
user: merve
- dataset:
id: likaixin/ScreenSpot-Pro
task_id: android_studio_macos
value: 50.0
source:
url: https://gui-agent.github.io/grounding-leaderboard/
name: ScreenSpot-Pro Leaderboard
user: merve
- dataset:
id: likaixin/ScreenSpot-Pro
task_id: autocad_windows
value: 14.7
source:
url: https://gui-agent.github.io/grounding-leaderboard/
name: ScreenSpot-Pro Leaderboard
user: merve
- dataset:
id: likaixin/ScreenSpot-Pro
task_id: blender_windows
value: 47.9
source:
url: https://gui-agent.github.io/grounding-leaderboard/
name: ScreenSpot-Pro Leaderboard
user: merve
- dataset:
id: likaixin/ScreenSpot-Pro
task_id: davinci_macos
value: 54.5
source:
url: https://gui-agent.github.io/grounding-leaderboard/
name: ScreenSpot-Pro Leaderboard
user: merve
- dataset:
id: likaixin/ScreenSpot-Pro
task_id: eviews_windows
value: 94.0
source:
url: https://gui-agent.github.io/grounding-leaderboard/
name: ScreenSpot-Pro Leaderboard
user: merve
- dataset:
id: likaixin/ScreenSpot-Pro
task_id: excel_macos
value: 40.6
source:
url: https://gui-agent.github.io/grounding-leaderboard/
name: ScreenSpot-Pro Leaderboard
user: merve
- dataset:
id: likaixin/ScreenSpot-Pro
task_id: fruitloops_windows
value: 42.1
source:
url: https://gui-agent.github.io/grounding-leaderboard/
name: ScreenSpot-Pro Leaderboard
user: merve
- dataset:
id: likaixin/ScreenSpot-Pro
task_id: illustrator_windows
value: 19.4
source:
url: https://gui-agent.github.io/grounding-leaderboard/
name: ScreenSpot-Pro Leaderboard
user: merve
- dataset:
id: likaixin/ScreenSpot-Pro
task_id: inventor_windows
value: 48.6
source:
url: https://gui-agent.github.io/grounding-leaderboard/
name: ScreenSpot-Pro Leaderboard
user: merve
- dataset:
id: likaixin/ScreenSpot-Pro
task_id: linux_common_linux
value: 48.0
source:
url: https://gui-agent.github.io/grounding-leaderboard/
name: ScreenSpot-Pro Leaderboard
user: merve
- dataset:
id: likaixin/ScreenSpot-Pro
task_id: macos_common_macos
value: 41.5
source:
url: https://gui-agent.github.io/grounding-leaderboard/
name: ScreenSpot-Pro Leaderboard
user: merve
- dataset:
id: likaixin/ScreenSpot-Pro
task_id: matlab_macos
value: 66.7
source:
url: https://gui-agent.github.io/grounding-leaderboard/
name: ScreenSpot-Pro Leaderboard
user: merve
- dataset:
id: likaixin/ScreenSpot-Pro
task_id: origin_windows
value: 27.4
source:
url: https://gui-agent.github.io/grounding-leaderboard/
name: ScreenSpot-Pro Leaderboard
user: merve
- dataset:
id: likaixin/ScreenSpot-Pro
task_id: photoshop_windows
value: 51.0
source:
url: https://gui-agent.github.io/grounding-leaderboard/
name: ScreenSpot-Pro Leaderboard
user: merve
- dataset:
id: likaixin/ScreenSpot-Pro
task_id: powerpoint_windows
value: 70.7
source:
url: https://gui-agent.github.io/grounding-leaderboard/
name: ScreenSpot-Pro Leaderboard
user: merve
- dataset:
id: likaixin/ScreenSpot-Pro
task_id: premiere_windows
value: 42.3
source:
url: https://gui-agent.github.io/grounding-leaderboard/
name: ScreenSpot-Pro Leaderboard
user: merve
- dataset:
id: likaixin/ScreenSpot-Pro
task_id: pycharm_macos
value: 55.1
source:
url: https://gui-agent.github.io/grounding-leaderboard/
name: ScreenSpot-Pro Leaderboard
user: merve
- dataset:
id: likaixin/ScreenSpot-Pro
task_id: quartus_windows
value: 35.6
source:
url: https://gui-agent.github.io/grounding-leaderboard/
name: ScreenSpot-Pro Leaderboard
user: merve
- dataset:
id: likaixin/ScreenSpot-Pro
task_id: solidworks_windows
value: 32.5
source:
url: https://gui-agent.github.io/grounding-leaderboard/
name: ScreenSpot-Pro Leaderboard
user: merve
- dataset:
id: likaixin/ScreenSpot-Pro
task_id: stata_windows
value: 46.9
source:
url: https://gui-agent.github.io/grounding-leaderboard/
name: ScreenSpot-Pro Leaderboard
user: merve
- dataset:
id: likaixin/ScreenSpot-Pro
task_id: unreal_engine_windows
value: 60.0
source:
url: https://gui-agent.github.io/grounding-leaderboard/
name: ScreenSpot-Pro Leaderboard
user: merve
- dataset:
id: likaixin/ScreenSpot-Pro
task_id: vivado_windows
value: 71.2
source:
url: https://gui-agent.github.io/grounding-leaderboard/
name: ScreenSpot-Pro Leaderboard
user: merve
- dataset:
id: likaixin/ScreenSpot-Pro
task_id: vmware_macos
value: 58.5
source:
url: https://gui-agent.github.io/grounding-leaderboard/
name: ScreenSpot-Pro Leaderboard
user: merve
- dataset:
id: likaixin/ScreenSpot-Pro
task_id: vscode_macos
value: 56.4
source:
url: https://gui-agent.github.io/grounding-leaderboard/
name: ScreenSpot-Pro Leaderboard
user: merve
- dataset:
id: likaixin/ScreenSpot-Pro
task_id: windows_common_windows
value: 32.1
source:
url: https://gui-agent.github.io/grounding-leaderboard/
name: ScreenSpot-Pro Leaderboard
user: merve
- dataset:
id: likaixin/ScreenSpot-Pro
task_id: word_macos
value: 85.7
source:
url: https://gui-agent.github.io/grounding-leaderboard/
name: ScreenSpot-Pro Leaderboard
user: merve
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