Instructions to use deepset/bert-small-mm_retrieval-question_encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deepset/bert-small-mm_retrieval-question_encoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="deepset/bert-small-mm_retrieval-question_encoder")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("deepset/bert-small-mm_retrieval-question_encoder") model = AutoModel.from_pretrained("deepset/bert-small-mm_retrieval-question_encoder") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 09a6797a0476e4437b4d46491f32357ae9462659e151b6d7c320e8696e64077e
- Size of remote file:
- 115 MB
- SHA256:
- 71b7b54f60f20321a084a6dacd28c7b7ba96705aced0c677afce9fbe50a4daf2
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