Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
Generated from Trainer
dataset_size:60341
loss:MultipleNegativesRankingLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use marroyo777/bge-99GPT-v1-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use marroyo777/bge-99GPT-v1-test with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("marroyo777/bge-99GPT-v1-test") sentences = [ "What is the focus of the research conducted by the MHCI x 99P Labs Capstone Team?", "To determine the destination of a given car based on an initial start position in time, we developed a Markov Model. We then creatively combined DBScan, K-NN, and XGboost algorithms to achieve accurate dwell time forecasts.", "Transportation networks touch all three pillars of sustainability. They shape our daily lives by connecting us to work, retail, and recreation; however, a system that does not connect everyone equitably reproduces social disparities.", "Two weeks of digging deep into exploratory, generative research\nWritten by the MHCI x 99P Labs Capstone TeamEdited by 99P Labs\nThe MHCI x 99P Labs Capstone Team is part of the Master of Human-Computer Interaction (MHCI) program at Carnegie Mellon University." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Ctrl+K