Sentence Similarity
sentence-transformers
PyTorch
ONNX
nomic_bert
feature-extraction
mteb
custom_code
Eval Results (legacy)
text-embeddings-inference
Instructions to use nomic-ai/nomic-embed-text-v1-ablated 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-v1-ablated with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("nomic-ai/nomic-embed-text-v1-ablated", 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
Add Sentence Transformers support
#2
by tomaarsen HF Staff - opened
Hello!
This PR is a near mirror of https://huggingface.co/nomic-ai/nomic-embed-text-v1/discussions/1, except this model already has a tokenizer. I did update the tokenizer config (512 -> 8192 max model length) & beyond that the changes are pretty much the same as the previous PR.
- Tom Aarsen
tomaarsen changed pull request status to open
zpn changed pull request status to merged