Image-to-Text
Transformers
PyTorch
English
Korean
multilingual
veld
feature-extraction
vision, language
pretrained model
custom_code
Instructions to use KETI-AIR/veld-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KETI-AIR/veld-base with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "image-to-text" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("image-to-text", model="KETI-AIR/veld-base", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("KETI-AIR/veld-base", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Add multilingual to the language tag
Browse filesHi! A PR to add multilingual to the language tag to improve the referencing.
README.md
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license: apache-2.0
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language: [en, ko]
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tags:
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# veld base
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language:
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- en
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- ko
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- multilingual
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license: apache-2.0
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tags:
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- vision, language
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- pretrained model
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- image-to-text
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# veld base
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