Instructions to use antoinelouis/crossencoder-t5-small-mmarcoFR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use antoinelouis/crossencoder-t5-small-mmarcoFR with sentence-transformers:
from sentence_transformers import CrossEncoder model = CrossEncoder("antoinelouis/crossencoder-t5-small-mmarcoFR") query = "Which planet is known as the Red Planet?" passages = [ "Venus is often called Earth's twin because of its similar size and proximity.", "Mars, known for its reddish appearance, is often referred to as the Red Planet.", "Jupiter, the largest planet in our solar system, has a prominent red spot.", "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." ] scores = model.predict([(query, passage) for passage in passages]) print(scores) - Notebooks
- Google Colab
- Kaggle
Download spiece.model from antoinelouis/crossencoder-t5-small-mmarcoFR: direct link, hf CLI and curl.
- Browser
- Download file 792 kB
-
https://huggingface.co/antoinelouis/crossencoder-t5-small-mmarcoFR/resolve/main/spiece.model
- Command line
-
hf download hf://antoinelouis/crossencoder-t5-small-mmarcoFR/spiece.model
-
curl -L -o spiece.model https://huggingface.co/antoinelouis/crossencoder-t5-small-mmarcoFR/resolve/main/spiece.model
792 kB
- Xet hash:
- e7463c1c6b7c46ae0de79b004f3d7318bf4307ef0bef4de3be2e38ae80fab160
- Size of remote file:
- 792 kB
- SHA256:
- d60acb128cf7b7f2536e8f38a5b18a05535c9e14c7a355904270e15b0945ea86
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