Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
Generated from Trainer
dataset_size:160000
loss:MarginDistillationLoss
text-embeddings-inference
Instructions to use zihoo/all-MiniLM-L6-v2-WMGPL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use zihoo/all-MiniLM-L6-v2-WMGPL with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("zihoo/all-MiniLM-L6-v2-WMGPL") sentences = [ "why is it a healthy thing to be in a dynamic work environment?", "Workplace Mindfulness In spite of the advancements in the field, a major limita tion of the extant research is the lack of an effective means to measure workplace mindfulness. Workplace mindfulness is particularly concerned with events in the workplace (e.g., work tasks and meetings) rather than with events occurring outside of the work setting, such as life situations (e.g., driv ing and showering). At work, employees are embedded in task-oriented workflows, processes, and employment rela tionships (Zivnuska et al., 2016). Hence, prior research has theorized that workplace mindfulness depends on the par ticular context—namely, the work environment (Dane & Brummel, 2014)—and focusing on this specific setting can help mindfulness scholars tackle issues of theoretical impor tance and practical concern (Dane, 2011; Dane & Brummel, 2014). Further, scholars have indicated that some employees may be more mindful at work than others due to specific experiences they have accrued (Dane & Brummel, 2014). It is therefore possible that, for some employees, certain fea tures and events in the workplace—that is, contextual stimuli encountered in this setting (Dane & Brummel, 2014; Ziv nuska et al., 2016)—may induce workplace mindfulness. As such, any measure of workplace mindfulness should essen tially capture an employee’s awareness and attention to the work-related issues that an individual encounters within the work setting (Elsbach & Pratt, 2007; George, 2009).", "Examining workplace mindfulness \nand its relations to job \nperformance and \nturnover intention Dynamic work environments tend to be associated with high levels of emotional arousal and stress – byproducts of the time pressure and unpredictability pervading such environments (Brehmer, 1992; Klein, 1998). Over time, these pressures may become difficult to bear, leading people to consider relinquishing their employment in the dynamic work setting. On this point, research demonstrates negative relationships between psychological and physiological job-related demands and people’s intentions to leave their organizations (Begley, 1998; Kemery et al., 1987). With that said, intention to leave (i.e. turnover intention) is subject to a number of influences, including not only features of the work context, but also individual-level factors (Cardador et al., 2011; Meyer et al., 2002). As such, even within the same work setting, people may differ in their turnover intentions.", "Workplace Mindfulness Mindfulness can also be conceptualized as a trait character ized by receptive awareness and attention to ongoing events and experiences (Brown & Ryan, 2003; Feldman et al., 2007). Compared with the traditional conceptualization of a trait, mindfulness as an individual difference is less stable and can be affected more by internal and external stimuli, though it remains more stable than a state. For instance, Brown and Ryan (2003, p. 823) indicated that mindfulness involves “an open, undivided observation of what is occurring both internally and externally.” Cardaciotto et al., (2008, p. 205)defined mindfulness as “the tendency to be highly aware of one’s internal and external experiences in the context of an accepting, nonjudgmental stance toward those experiences.”" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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