Sentence Similarity
sentence-transformers
ONNX
Safetensors
bert
feature-extraction
dense
Generated from Trainer
dataset_size:362
loss:CosineSimilarityLoss
text-embeddings-inference
Instructions to use pramudyalyza/asktoal-model-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use pramudyalyza/asktoal-model-v2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("pramudyalyza/asktoal-model-v2") sentences = [ "What's her experience like?", "What's her experience like?", "Alyza and her teammates delivered a 94% improvement in time efficiency.", "Alyza developed dashboards for Sell-In and Sell-Out analysis, analyzed and prepared sales data for meetings, collaborated on analyzing promotion-sales correlations, predicted future sales, analyzed stock on hand and offtake data, designed monthly sales plans, updated performance data, managed master data, created promotional cooperation letters, and addressed claim issues." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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