Update model metadata to set pipeline tag to the new `text-ranking` and library name to `sentence-transformers`
#3
by tomaarsen HF Staff - opened
Hello!
Pull Request overview
- Update metadata to set pipeline tag to the new
text-ranking - Update metadata to set library name to
sentence-transformers
Changes
This is an automated pull request to update the metadata of the model card. We recently introduced the text-ranking pipeline tag for models that are used for ranking tasks, and we have a suspicion that this model is one of them. I also updated added metadata to specify that this model can be loaded with the sentence-transformers library, as it should be possible to load any model compatible with transformers AutoModelForSequenceClassification.
Feel free to verify that it works with the following:
pip install sentence-transformers
from sentence_transformers import CrossEncoder
model = CrossEncoder("intfloat/simlm-msmarco-reranker")
scores = model.predict([
("How many people live in Berlin?", "Berlin had a population of 3,520,031 registered inhabitants in an area of 891.82 square kilometers."),
("How many people live in Berlin?", "Berlin is well known for its museums."),
])
print(scores)
Feel free to respond if you have questions or concerns.
- Tom Aarsen
intfloat changed pull request status to merged