Instructions to use facebook/spar-paq-bm25-lexmodel-query-encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/spar-paq-bm25-lexmodel-query-encoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="facebook/spar-paq-bm25-lexmodel-query-encoder")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("facebook/spar-paq-bm25-lexmodel-query-encoder") model = AutoModel.from_pretrained("facebook/spar-paq-bm25-lexmodel-query-encoder") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ac3b426d0de69df51082b9ca87f57b11d54772da59fd1744d67b0c2abadcd032
- Size of remote file:
- 438 MB
- SHA256:
- 8e31ac60c0f86e162cf5fe34bdb31254fffb43401a161195a16ddb874e2d5432
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