Sentence Similarity
sentence-transformers
Safetensors
nomic_bert
feature-extraction
custom_code
text-embeddings-inference
Instructions to use nomic-ai/nomic-embed-text-v2-moe with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use nomic-ai/nomic-embed-text-v2-moe with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("nomic-ai/nomic-embed-text-v2-moe", trust_remote_code=True) sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Upload model
Browse files- config.json +1 -1
- model.safetensors +1 -1
config.json
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"_name_or_path": "nomic-ai/nomic-
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"activation_function": "gelu",
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"add_pooling_layer": false,
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"architectures": [
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"_name_or_path": "nomic-ai/nomic-xlm-2048",
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"activation_function": "gelu",
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"add_pooling_layer": false,
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"architectures": [
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model.safetensors
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