How to use Master-thesis-NAP/ModernBERT-DAPT-Embed-DAPT-Math with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Master-thesis-NAP/ModernBERT-DAPT-Embed-DAPT-Math") sentences = [ "What is the error estimate for the difference between the exact solution and the local oscillation decomposition (LOD) solution in terms of the $L_0$ norm?", "\\label{RL1}\nThe system \\eqref{R3} has the following positive fixed points if $0 <\\alpha\\leq1$ and $b>d$\n$$E^*=\\left(\\dfrac{d}{b}, \\dfrac{(b-d) r}{b^2}\\right)$$", "\\label{theo1d}\nWith the assumptions and setting is this section, the finite difference solution computed using the improved harmonic average method applied to \\eqn{eq1d} or \\eqn{eq1dB} has second order convergence in the infinity norm, that is,\n\\eqm\n \\|\\mathbf{E} \\|_{\\infty}\\le C h^2,\n\\enm\nassuming that the true solution of \\eqn{eq1d} is piecewise $C^4$ excluding the interface $\\alf$, that is, \n$u(x) \\in C^4(0,\\alf) \\cup C^4(\\alf,1)$. \n%where $C$ is a generic error constant.", "\\label{Corollary}\n Let Assumptions~\\ref{assum_1} and~\\ref{assump2} be satisfied. Let $u$ be the solution of~\\eqref{WeakForm} and let $u_{H,k}$ be the LOD solution of~\\eqref{local_probelm }. Then we have \n \\begin{equation}\\label{L2Estimate}\n \\|u-I_Hu_{H,k}\\|_0\\lesssim \\|u-I_Hu\\|_0+\\|u-u_{H,k}\\|_0 +H|u-u_{H,k}|_1.\n \\end{equation}\n %\\[\\|u-I_Hu_{H,k}\\|_0\\lesssim H |u|_1 +|u-u_{H,k}|_1.\\]" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
