Instructions to use jinaai/xlm-roberta-flash-implementation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jinaai/xlm-roberta-flash-implementation with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("jinaai/xlm-roberta-flash-implementation", dtype="auto") - Notebooks
- Google Colab
- Kaggle
fix-normalization-after-truncate
#53
by jupyterjazz - opened
We had a bug in the encode function, doing Matryoshka embedding truncation after normalization, resulting in non-normalized truncated embeddings:
https://huggingface.co/jinaai/jina-embeddings-v3/discussions/60
This PR fixes the issue by moving normalization after truncation
jupyterjazz changed pull request status to open
The changes look good ๐ thanks for making the fix!
jupyterjazz changed pull request status to merged