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")# pip install -U transformers accelerate # 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", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Commit History
-
Adding `safetensors` variant of this model (#1)
- Adding `safetensors` variant of this model (48bb29cd6b7e60ee4c946cefe8950590703091a2) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>9c9246a
-
initial commit
7049dfa