Instructions to use Anvilogic/Embedder-Typosquat-Detect with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Anvilogic/Embedder-Typosquat-Detect with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Anvilogic/Embedder-Typosquat-Detect") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
GGUF Format
#1
by kalle07 - opened
at the moment not possible , you have any idea ?
Hmm this is a tricky one ,this model was made with CANINE model as the problem we solve is sensitive to slight letter change. I dont know how well GGUF support CANINE architectures. Mybe an onnx optimized custom model would be a better solution