Model: DigitalAsocial/all-mpnet-base-v2-ds-rag-17g
Author: DigitalAsocial
Pipeline: sentence-similarity
Library: sentence-transformers
Tags: sentence-transformers, safetensors, mpnet, Data-Science, Machine-Learning, sentence-similarity, feature-extraction, dense, generated_from_trainer, dataset_size:167112, loss:MultipleNegativesRankingLoss, en, dataset:DigitalAsocial/ds-tb-17-g, arxiv:1908.10084, arxiv:1705.00652, base_model:sentence-transformers/all-mpnet-base-v2, base_model:finetune:sentence-transformers/all-mpnet-base-v2, license:apache-2.0, model-index, endpoints_compatible, region:us
Base models (finetune): id: sentence-transformers/all-mpnet-base-v2
Card metadata: tags: Data-Science, Machine-Learning, sentence-transformers, sentence-similarity, feature-extraction, dense, generated_from_trainer, dataset_size:167112, loss:MultipleNegativesRankingLoss
widget: source_sentence: We can actually think of finding the best discriminant function as the task of finding the best distance function.
sentences: This is another example of bias/variance dilemma., This process is repeated until only C K remains., A central issue here is to estimate an m-dimensional random vector θ, using optimal sequential selection of observations, which are based on feedback from preceding observations; see Fig., source_sentence: This remains true even if we introduce discounting.
sentences: Since the diffusion model is stochastic by nature, it's possible to generate multiple images that are conditioned on the same caption., The investor wants to maximize the expected value of the sale., Thus, we can define the return, in general, according to (3.2), using the convention of omitting episode numbers when they are not needed, and including the possibility that γ = 1 if the sum remains defined (e.g., because all episodes terminate)., source_sentence: With DCGAN, Radford and his collaborators introduced techniques and optimizations that allowed ConvNets to scale up to the full GAN framework without the need to modify the underlying GAN architecture and without reducing GAN to a subroutine of a more complex model framework, like LAPGAN.
sentences: We can define a discriminant function as

We can write the discriminant as the product of the likelihood ratio and the ratio of priors:

If the priors are equal, the discriminant is the likelihood ratio., For the generator, the attribute c can be appended to the latent vector z., Let's take a closer look at what batch normalization is and how it works., source_sentence: Suppose ||u|| = 1, so that u is a unit vector.
sentences: Importantly, for semi-supervised learning to work, the labeled and unlabeled data must come from the same underlying distribution., For example, in the context 'strings_of_ch', one might predict the next nine symbols to be 'aracters_' with a probability of 0.99 each., We can think of any other vector v as consisting of two components: (a) a component in the direction of u and (b) a component that's perpendicular to u., source_sentence: In doing this, there are three decisions we must make:

1.
sentences: g(•) defines the hypothesis class H , and a particular value of θ instantiates one hypothesis h ∈ H ., Although replacing traces (Section 7.8) are known to have advantages in tabular methods, replacing traces do not directly extend to the use of function approximation., Samples are also used in tests of various sorts (e.g., pricing, web treatments).
pipeline_tag: sentence-similarity
library_name: sentence-transformers
metrics: pearson_cosine, spearman_cosine
model-index: name: SentenceTransformer
results: task: type: semantic-similarity
name: Semantic Similarity
dataset: name: val
type: val
metrics: type: pearson_cosine
name: Pearson Cosine
verified: no, type: spearman_cosine
name: Spearman Cosine
verified: no
license: apache-2.0
language: en
base_model: sentence-transformers/all-mpnet-base-v2
datasets: DigitalAsocial/ds-tb-17-g
Likes: 0 | All-time downloads: 16
Created: 2025-12-02 01:26:43