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
Adding `safetensors` variant of this model
#2
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:25dd68d4c8e211681581d81647ef97263dd5cfb17da98e50e60621a19fcb81a1
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size 1353647944
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