Instructions to use ibm-research/re2g-qry-encoder-nq with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ibm-research/re2g-qry-encoder-nq with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="ibm-research/re2g-qry-encoder-nq")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("ibm-research/re2g-qry-encoder-nq") model = AutoModel.from_pretrained("ibm-research/re2g-qry-encoder-nq", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4ae5924d7c63944058d82a41bae74c22ca53fcdddbef2accdb416851bd415b82
- Size of remote file:
- 438 MB
- SHA256:
- dc0e9d706677446752ed8aa227371ee97c0a5646a4b450d086ac965e7d3b7946
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