Sentence Similarity
sentence-transformers
Safetensors
feature-extraction
dense
Generated from Trainer
dataset_size:2680
loss:MultipleNegativesRankingLoss
Instructions to use blachang28/my-embedding-gemma with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use blachang28/my-embedding-gemma with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("blachang28/my-embedding-gemma") sentences = [ "Let $A, M,$ and $C$ be nonnegative integers such that $A + M + C = 12$. What is the maximum value of $A \\cdot M \\cdot C + A \\cdot M + M \\cdot C + A \\cdot C$?", "Given that $2^{2004}$ is a $604$-digit number whose first digit is $1$, how many elements of the set $S = \\{2^0,2^1,2^2,\\ldots ,2^{2003}\\}$ have a first digit of $4$?", "To complete the grid below, each of the digits 1 through 4 must occur once in each row and once in each column. What number will occupy the lower right-hand square? \\[\\begin{tabular}{|c|c|c|c|}\\hline 1 & & 2 &\\\\ \\hline 2 & 3 & &\\\\ \\hline & &&4\\\\ \\hline & &&\\\\ \\hline\\end{tabular}\\]", "Two non-zero real numbers, $a$ and $b,$ satisfy $ab = a - b$. Which of the following is a possible value of $\\frac {a}{b} + \\frac {b}{a} - ab$?" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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