Instructions to use Wakeleyhuh/chowder-embed-specter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Wakeleyhuh/chowder-embed-specter with sentence-transformers:

from sentence_transformers import SentenceTransformer

model = SentenceTransformer("Wakeleyhuh/chowder-embed-specter")

sentences = [
    "The hyperspace ω(f) when f is a transitive dendrite mapping",
    "Knee osteoarthritis (OA) is a major cause of chronic pain and disability in older adults, yet scalable home-based interventions remain limited, partly due to the lack of clinically effective digital solutions. This study is the first fully powered randomized, double-blind, sham-controlled trial to test a digitally delivered, home-based protocol combining transcranial direct current stimulation (tDCS) and mindfulness-based meditation (MBM) for knee OA pain. A total of 208 participants were randomized to active tDCS + MBM, active tDCS + sham MBM, sham tDCS + active MBM, or double sham; they completed ten 20-min sessions over 2 weeks. Knee pain intensity was measured at baseline, post treatment, and monthly for 3 months. Although both active tDCS groups improved, the difference between the combined tDCS + MBM intervention and tDCS alone was not statistically significant. Benefits were not sustained at 3 months. These findings offer the first evidence that a remotely supervised, digitally delivered tDCS + MBM intervention can rapidly reduce knee OA pain, supporting future personalized and extended treatment studies. Clinical trial registration: ClinicalTrials.gov NCT04375072 (registered May 7, 2020).",
    "  Let $X$ be a compact metric space. By $2^X$ we denote the hyperspace of all\nclosed and non-empty subsets of $X$ endowed with the Hausdorff metric. Let\n$f:X\\to X$ be a continuous function. In this paper we study some topological\nproperties of the hyperspace $\\omega(f)$, the collection of all omega limits\nsets $\\omega(x,f)$ with $x\\in X$. We prove the following: $i)$ If $X$ has no\nisolated points, then, for every continuous function $f:X\\to X$,\n$int_{2^X}(\\omega(f))=\\emptyset$. $ii)$ If $X$ is a dendrite for which every\narc contains a free arc and $f:X\\to X$ is transitive, then the hyperspace\n$\\omega(f)$ is totally disconnected. $iii)$ Let $D_\\infty$ be the Wazewski's\nuniversal dendrite. Then there exists a transitive continuous function\n$f:D_\\infty\\to D_\\infty$ for which the hyperspace $\\omega(f)$ contains an arc;\nhence, $\\omega(f)$ is not totally disconnected.\n",
    "Let $X_1,\\,X_2,\\,\\ldots,\\,X_N$, $N\\in\\mathbb N$ be independent, discrete, integer-valued random variables. Assume that $X_j\\geqslant m_j$ almost surely for each $j=1,\\,2,\\,\\ldots,\\,N$, where $m_1,\\,m_2,\\,\\ldots,\\,m_N\\in\\mathbb{Z}$ satisfy $m_1+\\cdots+m_N<0$. Furthermore, suppose that the sequence $X_1,\\,X_2,\\,\\ldots$ is periodic in distribution, i.e. $X_k{\\buildrel d \\over =} X_{k+N}$ for all $k\\in\\mathbb N$. We derive computable representations for the distribution functions of $\\max\\{X_1,\\,X_1+X_2,\\,\\ldots\\}$, $\\max\\{X_2,\\,X_2+X_3,\\,\\ldots\\}$, $\\ldots$, $\\max\\{X_N,\\,X_N+X_{N+1},\\,\\ldots\\}$. The obtained formulas are based on a linear recurrence whose initial values are determined from a linear system that involves the roots of an associated characteristic equation and the distributions of $X_1,\\,X_2,\\,\\ldots,\\,X_N$. Several examples are presented, including a biseasonal-biased Rademacher random walk for which the distribution, generating functions, and all moments admit explicit closed-form expressions. In addition, we identify and correct several inaccuracies in the results reported in \\cite{Grigutis2024}."
]
embeddings = model.encode(sentences)

similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [4, 4]

Notebooks
Google Colab
Kaggle

Wakeleyhuh commited on 1 day ago

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