Instructions to use jcwang0602/MLLMSeg_InternVL2_5_2B_RES with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jcwang0602/MLLMSeg_InternVL2_5_2B_RES with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="jcwang0602/MLLMSeg_InternVL2_5_2B_RES", trust_remote_code=True)# Load model directly from transformers import MLLMSeg model = MLLMSeg.from_pretrained("jcwang0602/MLLMSeg_InternVL2_5_2B_RES", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Unexpected keyword argument 'output_segmentation_mask'
#2
by thewiseqzy - opened
InternVLChatModel.chat() got an unexpected keyword argument 'output_segmentation_mask'
File "/mnt/sevenT/qinbinl/qzy/Cloud-Edge/agentos/resource/large_seg.py", line 106, in
response, history, pred_mask = model.chat(tokenizer, pixel_values, question, generation_config, history=None, return_history=True, output_segmentation_mask=True)
TypeError: InternVLChatModel.chat() got an unexpected keyword argument 'output_segmentation_mask'
Thank you for your attention to our work. Currently, there are some issues with this demo on Hugging Face that have not been resolved yet. You can try it by using the code in GitHub. https://github.com/jcwang0602/MLLMSeg