Image Feature Extraction
Transformers
Safetensors
English
Korean
vision-encoder
multimodal
custom_code
Instructions to use skt/A.X-VE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use skt/A.X-VE with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="skt/A.X-VE", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("skt/A.X-VE", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 684 Bytes
d6a610e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | from transformers.models.auto import (
AutoConfig,
AutoModel,
AutoProcessor,
AutoImageProcessor,
)
from .configuration_ax_ve import AXVEConfig
from .configuration_ax_ve import AXVEVisionConfig
from .modeling_ax_ve import AXVEVisionModel
from .processing_ax_ve import AXVEProcessor
from .image_processing_ax_ve import AXVEImageProcessor
AutoConfig.register(AXVEConfig.model_type, AXVEConfig)
AutoConfig.register(AXVEVisionConfig.model_type, AXVEVisionConfig)
AutoModel.register(AXVEVisionConfig, AXVEVisionModel)
AutoProcessor.register(AXVEConfig, AXVEProcessor)
AutoImageProcessor.register(AXVEConfig, AXVEImageProcessor)
print("A.X VE vision encoder registered")
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