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Hyukkyu/nv-embed-v2
nv-embed-v2 is a feature extraction model from Hyukkyu. Use it when you need embeddings to search or compare text. It is set up for transformers. The card lists the license as cc-by-nc-4.0.
This is a migrated version of nvidia/NV-Embed-v2 that is compatible with transformers 5.0.0 and later versions.
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From the Hugging Face model README
This is a migrated version of nvidia/NV-Embed-v2 that is compatible with transformers 5.0.0 and later versions.
The only change made is adding an all_tied_weights_keys property to the NVEmbedModel class in modeling_nvembed.py. This property provides backward compatibility with the transformers library, which changed from using _tied_weights_keys (a class attribute) to all_tied_weights_keys (a property that returns a dict) in version 5.0.0.
@property
def all_tied_weights_keys(self):
"""Compatibility property for transformers >= 5.0.0."""
if hasattr(self, '_tied_weights_keys') and self._tied_weights_keys:
return {key: key for key in self._tied_weights_keys}
return {}
from transformers import AutoModel, AutoTokenizer
model = AutoModel.from_pretrained("Hyukkyu/nv-embed-v2", trust_remote_code=True)
tokenizer = AutoTokenizer.from_pretrained("Hyukkyu/nv-embed-v2", trust_remote_code=True)
This model is based on nvidia/NV-Embed-v2. Please refer to the original repository for:
This model inherits the license from the original repository. Please check nvidia/NV-Embed-v2 for license details.
This model was migrated using the GenZ model migration tool. The migration script is available at: https://github.com/your-repo/GenZ/tree/main/scripts/preprocess/model