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
File size: 347 Bytes
aaa3161 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | {
"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"
} |