sabafallah

/

bge-reranker-v2-m3-Q4_K_M-GGUF

like 0

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("sabafallah/bge-reranker-v2-m3-Q4_K_M-GGUF")
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