Instructions to use ibm-granite/granite-vision-3.3-2b-embedding with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ibm-granite/granite-vision-3.3-2b-embedding with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="ibm-granite/granite-vision-3.3-2b-embedding", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ibm-granite/granite-vision-3.3-2b-embedding", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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import torch
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from PIL import Image
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from transformers import AutoProcessor, AutoModel
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device = "cuda" if torch.cuda.is_available() else "cpu"
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model_name = "ibm-granite/granite-vision-3.3-2b-embedding"
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import torch
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from PIL import Image
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from transformers import AutoProcessor, AutoModel
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from transformers.utils.import_utils import is_flash_attn_2_available
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device = "cuda" if torch.cuda.is_available() else "cpu"
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model_name = "ibm-granite/granite-vision-3.3-2b-embedding"
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