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:
- e409fbb63f3248933a77778a4d5349f033da24e7782098c1d056698e9b9cff8a
- Size of remote file:
- 115 MB
- SHA256:
- 88ddc04b664c0a0c8b3e0005312a274d78081b72252fb5d9b6c9d87f7b4ef332
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