Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
Generated from Trainer
dataset_size:133380
loss:CosineSimilarityLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use vazish/all-Mini-fine-tuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use vazish/all-Mini-fine-tuned with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("vazish/all-Mini-fine-tuned") sentences = [ "Plant-Based Nutrition Guide", "Streaming Videos about Miscellaneous", "Honest John - Car Reviews & Buying Advice", "Participating in online forums and communities about Seasonal Forecasts" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Welcome to the community
The community tab is the place to discuss and collaborate with the HF community!