Instructions to use shomez/blink-biencoder-description-encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shomez/blink-biencoder-description-encoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="shomez/blink-biencoder-description-encoder")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("shomez/blink-biencoder-description-encoder") model = AutoModel.from_pretrained("shomez/blink-biencoder-description-encoder", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload model.onnx with huggingface_hub
Browse files- model.onnx +3 -0
model.onnx
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version https://git-lfs.github.com/spec/v1
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oid sha256:85b3d7832309f59bd9638bc15a9cf3a365a220721e35fcb2d73dee36373f7031
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size 1336918758
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