Instructions to use CUDAOUTOFMEMORY/PLUME-Qwen2-VL-2B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CUDAOUTOFMEMORY/PLUME-Qwen2-VL-2B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="CUDAOUTOFMEMORY/PLUME-Qwen2-VL-2B")# Load model directly from transformers import AutoProcessor, AutoModelForImageTextToText processor = AutoProcessor.from_pretrained("CUDAOUTOFMEMORY/PLUME-Qwen2-VL-2B") model = AutoModelForImageTextToText.from_pretrained("CUDAOUTOFMEMORY/PLUME-Qwen2-VL-2B") - Notebooks
- Google Colab
- Kaggle
| { | |
| "min_pixels": 3136, | |
| "max_pixels": 12845056, | |
| "patch_size": 14, | |
| "temporal_patch_size": 2, | |
| "merge_size": 2, | |
| "image_mean": [ | |
| 0.48145466, | |
| 0.4578275, | |
| 0.40821073 | |
| ], | |
| "image_std": [ | |
| 0.26862954, | |
| 0.26130258, | |
| 0.27577711 | |
| ], | |
| "image_processor_type": "Qwen2VLImageProcessor", | |
| "processor_class": "Qwen2VLProcessor" | |
| } |