Sentence Similarity
sentence-transformers
PyTorch
Transformers
mpnet
feature-extraction
sentence-classifier
sentiment-classifier
text-embeddings-inference
Instructions to use nixmaverick1997/app-setfit-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use nixmaverick1997/app-setfit-classifier with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("nixmaverick1997/app-setfit-classifier") 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] - Transformers
How to use nixmaverick1997/app-setfit-classifier with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("nixmaverick1997/app-setfit-classifier") model = AutoModel.from_pretrained("nixmaverick1997/app-setfit-classifier") - Notebooks
- Google Colab
- Kaggle
Commit History
Update README.md fe1c8bb
Baseline model notebook 514811d
Update README.md a652537
Update README.md 5cba335
Create app.py 0cce1c7
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