Feature Extraction
sentence-transformers
PyTorch
ONNX
Safetensors
English
bert
mteb
sentence-similarity
Eval Results (legacy)
text-embeddings-inference
Instructions to use vectoriseai/ember-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use vectoriseai/ember-v1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("vectoriseai/ember-v1") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
Query Regarding Paper
#1
by KhushKrishna - opened
Hello
I have used ember-v1 to perform Sentiment analysis for various domains. I want to write a research paper based on my experiments with this model. For this I need more details about the working principle/techniques behind ember-v1 so that i can write those details in my research paper. Can anyone please help? However it is mentioned that ember-v1 paper will be published soon but any idea how long will it take.