Sentence Similarity
sentence-transformers
TensorBoard
Safetensors
mpnet
feature-extraction
Generated from Trainer
dataset_size:32351
loss:TripletLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use hmm404/tmp_trainer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use hmm404/tmp_trainer with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("hmm404/tmp_trainer") sentences = [ "Genetic conditions that cause nutritional deficiencies can prevent a person from removing meat from their diet.", "Ante un estado que no quiere hablar del tema, para Cataluña, solo es posible seguir su propio camino por otras vías.", "Retinol deficiency is a genetically pre-disposed condition that prevents conversion beta-carotene to Vitamin A \\(retinol\\) in humans. Since plants have no retinol \\(only beta-carotene\\), humans with this condition cannot have a vegan diet, only one with animal products.", "People with hemochromatosis \\(a genetic condition\\) can benefit greatly from a vegan diet, due to the lower absorbing non-heme iron in plants \\(compared to heme iron in meat\\)." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle