Instructions to use nvidia/NV-Embed-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use nvidia/NV-Embed-v1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("nvidia/NV-Embed-v1", trust_remote_code=True) sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
AttributeError: 'NVEmbedConfig' object has no attribute 'hidden_size'
File "/mnt/cache/zhangxingyan/env/emb/lib/python3.10/site-packages/sentence_transformers/SentenceTransformer.py", line 298, in init
modules = self._load_auto_model(
File "/mnt/cache/zhangxingyan/env/emb/lib/python3.10/site-packages/sentence_transformers/SentenceTransformer.py", line 1319, in _load_auto_model
pooling_model = Pooling(transformer_model.get_word_embedding_dimension(), "mean")
File "/mnt/cache/zhangxingyan/env/emb/lib/python3.10/site-packages/sentence_transformers/models/Transformer.py", line 133, in get_word_embedding_dimension
return self.auto_model.config.hidden_size
File "/mnt/cache/zhangxingyan/env/emb/lib/python3.10/site-packages/transformers/configuration_utils.py", line 264, in getattribute
return super().getattribute(key)
AttributeError: 'NVEmbedConfig' object has no attribute 'hidden_size'
ERROR: Application startup failed. Exiting.
Thanks for reporting the issue. Currently, sentence transformer is not supported, but we will try to add the sentence transformer compatibility soon.
Now, NV-Embed-v1 supports the compatibility for sentence transformer. The example is updated in model card: https://huggingface.co/nvidia/NV-Embed-v1. Thank you.
File "/home/tlv/duplicate-content-checker/tests/models_test/evaluation.py", line 40, in
evaluation(
File "/home/tlv/duplicate-content-checker/tests/models_test/evaluation.py", line 20, in evaluation
model = SentenceTransformer(model_name, trust_remote_code=True, device=device)
File "/home/tlv/duplicate-content-checker/venv/lib/python3.10/site-packages/sentence_transformers/SentenceTransformer.py", line 205, in init
modules = self._load_auto_model(
File "/home/tlv/duplicate-content-checker/venv/lib/python3.10/site-packages/sentence_transformers/SentenceTransformer.py", line 1203, in _load_auto_model
pooling_model = Pooling(transformer_model.get_word_embedding_dimension(), "mean")
File "/home/tlv/duplicate-content-checker/venv/lib/python3.10/site-packages/sentence_transformers/models/Transformer.py", line 114, in get_word_embedding_dimension
return self.auto_model.config.hidden_size
File "/home/tlv/duplicate-content-checker/venv/lib/python3.10/site-packages/transformers/configuration_utils.py", line 263, in getattribute
return super().getattribute(key)
AttributeError: 'NVEmbedConfig' object has no attribute 'hidden_size'
Hello, I still have this issue. My SentenceTransformers is v3.0.1 now.