Robotics
Transformers
Safetensors
English
glm4v
image-text-to-text
computer-vision
spatial-reasoning
vision-language-model
multi-modal
fine-tuned
Instructions to use hany01rye/TIGeR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hany01rye/TIGeR with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("hany01rye/TIGeR") model = AutoModelForMultimodalLM.from_pretrained("hany01rye/TIGeR", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download requirements.txt from hany01rye/TIGeR: direct link, hf CLI and curl.
- Browser
- Download file 165 Bytes
-
https://huggingface.co/hany01rye/TIGeR/resolve/main/requirements.txt
- Command line
-
hf download hf://hany01rye/TIGeR/requirements.txt
-
curl -L -o requirements.txt https://huggingface.co/hany01rye/TIGeR/resolve/main/requirements.txt
165 Bytes
| torch>=2.0.0 | |
| transformers>=4.55.0 | |
| pillow>=9.0.0 | |
| opencv-python>=4.5.0 | |
| numpy>=1.21.0 | |
| huggingface_hub>=0.20.0 | |
| accelerate>=0.25.0 | |
| safetensors>=0.4.0 | |
| llamafactory>=0.8.0 | |