Sentence Similarity
sentence-transformers
PyTorch
bert
feature-extraction
setfit classification
binary_classification
text-embeddings-inference
Instructions to use nayan06/binary-classifier-conversion-intent-1.0 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-1.0 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("nayan06/binary-classifier-conversion-intent-1.0") 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
Download tokenizer.json from nayan06/binary-classifier-conversion-intent-1.0: direct link, hf CLI and curl.
- Browser
- Download file 712 kB
-
https://huggingface.co/nayan06/binary-classifier-conversion-intent-1.0/resolve/refs%2Fpr%2F1/tokenizer.json
- Command line
-
hf download hf://nayan06/binary-classifier-conversion-intent-1.0@refs/pr/1/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/nayan06/binary-classifier-conversion-intent-1.0/resolve/refs%2Fpr%2F1/tokenizer.json
712 kB
File too large to display, you can check the raw version instead.