Instructions to use BAAI/llm-embedder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BAAI/llm-embedder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="BAAI/llm-embedder")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("BAAI/llm-embedder") model = AutoModel.from_pretrained("BAAI/llm-embedder") - Inference
- Notebooks
- Google Colab
- Kaggle
Add exported onnx model 'model_qint8_avx512.onnx'
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by Narsil - opened
onnx/model_qint8_avx512.onnx
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version https://git-lfs.github.com/spec/v1
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oid sha256:40b7a0173ee7d879a4e0b0dd72dd07a4d40b19b2182829f3b56e293b0aaffbd2
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size 110187550
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