all-MiniLM-L6-v2-multi-qa-slerp-merge
A demonstration model produced by the native model-merging feature (SentenceTransformer.merge)
added to Sentence Transformers. It spherically interpolates (slerp) between the two models at t = 0.5.
Merged checkpoints:
How it was created
from sentence_transformers import SentenceTransformer
merged = SentenceTransformer.merge(
models=["sentence-transformers/all-MiniLM-L6-v2",
"sentence-transformers/multi-qa-MiniLM-L6-cos-v1"],
weights=[0.5, 0.5],
method="slerp",
output_path="all-MiniLM-L6-v2-multi-qa-slerp-merge",
dtype="float32",
)
Usage
from sentence_transformers import SentenceTransformer
model = SentenceTransformer("yjoonjang/all-MiniLM-L6-v2-multi-qa-slerp-merge")
emb = model.encode(["Model merging combines fine-tuned checkpoints.",
"It often beats each individual model."])
print(model.similarity(emb, emb))
License
Derivative of the two base models above; their licenses apply. See each base model's card.