Instructions to use Corran/SciTopicNomicEmbedStatic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Model2Vec
How to use Corran/SciTopicNomicEmbedStatic with Model2Vec:
from model2vec import StaticModel model = StaticModel.from_pretrained("Corran/SciTopicNomicEmbedStatic") - sentence-transformers
How to use Corran/SciTopicNomicEmbedStatic with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Corran/SciTopicNomicEmbedStatic") 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
- Xet hash:
- f04ddc17a1ede2fece3750e1bbe8f1302b22264e647f36381478429b4a00766a
- Size of remote file:
- 90.7 MB
- SHA256:
- 4fdc22c188097d45e4a262d052686bb4cc2c8b031e2f8b970096f1bac9e306d6
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