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
Splinter Memory: the white paper as the model card (long-context memory curation management)
69ff84b verified Download figures/flow.png from SkyIsNotGreen/splinter-memory: direct link, hf CLI and curl.
- Browser
- Download file 135 kB
-
https://huggingface.co/SkyIsNotGreen/splinter-memory/resolve/main/figures/flow.png
- Command line
-
hf download hf://SkyIsNotGreen/splinter-memory/figures/flow.png
-
curl -L -o flow.png https://huggingface.co/SkyIsNotGreen/splinter-memory/resolve/main/figures/flow.png
135 kB

- Xet hash:
- 47a324daca2e2c3daea601ed0576092329db4848b3756d63148459b8ee0cf001
- Size of remote file:
- 135 kB
- SHA256:
- 8dc02e0884d76398573fd86120b22c024a14bf1e869c50fe48c548f074eeceee
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