Instructions to use SagaEmbed/saga-embed_v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use SagaEmbed/saga-embed_v1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("SagaEmbed/saga-embed_v1") 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
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README.md
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- **Retrieval (Queries):** `task: retrieval | query: {text}`
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- **Retrieval (Passages):** `title: none | text: {text}`
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- **Semantic Similarity:** `task: semantic similarity | query: {text}`
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```python
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- **Retrieval (Queries):** `task: retrieval | query: {text}`
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- **Retrieval (Passages):** `title: none | text: {text}`
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- **Clustering:** `task: clustering | query: {text}`
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- **Classification:** `task: classification | query: {text}`
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- **Semantic Similarity:** `task: semantic similarity | query: {text}`
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```python
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