Sentence Similarity
sentence-transformers
PyTorch
Transformers
mpnet
feature-extraction
text-embeddings-inference
Instructions to use nayan06/binary-classifier-conversion-intent-1.1-mpnet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use nayan06/binary-classifier-conversion-intent-1.1-mpnet with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("nayan06/binary-classifier-conversion-intent-1.1-mpnet") 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 nayan06/binary-classifier-conversion-intent-1.1-mpnet with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("nayan06/binary-classifier-conversion-intent-1.1-mpnet") model = AutoModel.from_pretrained("nayan06/binary-classifier-conversion-intent-1.1-mpnet", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 129 Bytes
cae60ab | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:954e7b6c85e9f6ee475724932661ed49e9e00bd20751c00e931c4d6a580ac3f0
size 7118
|