Image Feature Extraction
Transformers
Safetensors
English
qwen2_5_vl
image-text-to-text
mmeb
multimodal
reasoning
text-generation-inference
Instructions to use MCG-NJU/RGE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MCG-NJU/RGE with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="MCG-NJU/RGE")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("MCG-NJU/RGE") model = AutoModelForMultimodalLM.from_pretrained("MCG-NJU/RGE", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from MCG-NJU/RGE: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/MCG-NJU/RGE/resolve/main/tokenizer.json
- Command line
-
hf download hf://MCG-NJU/RGE/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/MCG-NJU/RGE/resolve/main/tokenizer.json
11.4 MB
- Xet hash:
- fd90c775ae1e580faee96d984ea8b51513c1e13d0cfd86ac5a5abc0b2b8db705
- Size of remote file:
- 11.4 MB
- SHA256:
- 267c6a3389803e16b650a03ade145bed1cb799da2b9b271c0bbd6d0d05639088
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