Instructions to use Intel/intel-optimized-model-for-embeddings-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Intel/intel-optimized-model-for-embeddings-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Intel/intel-optimized-model-for-embeddings-v1")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Intel/intel-optimized-model-for-embeddings-v1") model = AutoModel.from_pretrained("Intel/intel-optimized-model-for-embeddings-v1") - Notebooks
- Google Colab
- Kaggle
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README.md
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### Model Description
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This model was fine-tuned using the [sentence-transformers](https://github.com/UKPLab/sentence-transformers) library
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### Training Datasets
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### Model Description
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This model was fine-tuned using the [sentence-transformers](https://github.com/UKPLab/sentence-transformers) library
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based on the [BERT-Medium_L-8_H-512_A-8](https://huggingface.co/nreimers/BERT-Medium_L-8_H-512_A-8) model
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using [UAE-Large-V1](https://huggingface.co/WhereIsAI/UAE-Large-V1) as a teacher.
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### Training Datasets
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