Instructions to use jcwang0602/MLLMSeg_InternVL2_5_1B_RES with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jcwang0602/MLLMSeg_InternVL2_5_1B_RES with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="jcwang0602/MLLMSeg_InternVL2_5_1B_RES", trust_remote_code=True)# Load model directly from transformers import MLLMSeg model = MLLMSeg.from_pretrained("jcwang0602/MLLMSeg_InternVL2_5_1B_RES", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from jcwang0602/MLLMSeg_InternVL2_5_1B_RES: direct link, hf CLI and curl.
- Browser
- Download file 7.03 MB
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https://huggingface.co/jcwang0602/MLLMSeg_InternVL2_5_1B_RES/resolve/main/tokenizer.json
- Command line
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hf download hf://jcwang0602/MLLMSeg_InternVL2_5_1B_RES/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/jcwang0602/MLLMSeg_InternVL2_5_1B_RES/resolve/main/tokenizer.json
7.03 MB
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