#702 feat: Add ibm-granite/granite-embedding-small-english-r2 model

Resolves #701

Description

Adds support for the ibm-granite/granite-embedding-small-english-r2 model using the ONNX Community exported weights. This is a highly requested, very lightweight embedding model that punches well above its weight class on the MTEB leaderboard.

All Submissions:

• Have you followed the guidelines in our Contributing document?
• Have you checked to ensure there aren't other open Pull Requests for the same update/change?

New Feature Submissions:

• Does your submission pass the existing tests?
• Have you added tests for your feature?
• Have you installed pre-commit with pip3 install pre-commit and set up hooks with pre-commit install?

New models submission:

• Have you added an explanation of why it's important to include this model?
• Have you added tests for the new model? Were canonical values for tests computed via the original model?
• Have you added the code snippet for how canonical values were computed?
• Have you successfully ran tests with your changes locally?

from sentence_transformers import SentenceTransformer

model = SentenceTransformer("ibm-granite/granite-embedding-small-english-r2")
embeddings = model.encode(["hello world", "flag embedding"])

print(list(embeddings[0][:5]))
# Output: [0.47021756, -0.08181943, -0.97021246, 0.10116885, -0.16487208]