How to use nvidia/NV-Embed-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="nvidia/NV-Embed-v2", trust_remote_code=True)
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("nvidia/NV-Embed-v2", trust_remote_code=True, dtype="auto")
How to use nvidia/NV-Embed-v2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("nvidia/NV-Embed-v2", 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]
Hi! I would like to ask if there is a way for us users to further fine-tune this embedding model (e.g., using contrastive learning). Do you open-source the script, or is there a plan to open-source it? Thanks.
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