Sentence Similarity
sentence-transformers
context-curation
long-context
memory-management
conversational-ai
retrieval
llm
research-paper
Instructions to use SkyIsNotGreen/splinter-memory with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use SkyIsNotGreen/splinter-memory with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("SkyIsNotGreen/splinter-memory") 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
Commit History
Yesterday
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Update the card to the Cascade-edition white paper
hive-devAdd the Cascade-style title/deck, opening, contents, one-page claim table and three headline results. Rename the sections, reorder the encoder subsections, add explicit limits/what-is-not-claimed and a separate Reproduce section, sync the canonical-paper and repository links, and correct the 35B verdict-set and 93.9% replay recall statements.970b4e6
17 days ago
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Point the citation at the Hive monorepo
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The canonical project lives in the Hive repo under splinter/
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18 days ago
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Correct the card before publication: withdrawal of the invalidated drift numbers and the rejected threshold recommendation
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Update SkyIsNotGreen/splinter-memory from the HiveBench Studio
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19 days ago
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Release from the HiveBench Studio (private)
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Update README.md
Verified signatureFixed formatting.34a3f48 -
Splinter Memory: the white paper as the model card (long-context memory curation management)
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