Sentence Similarity
sentence-transformers
PyTorch
Transformers
bert
feature-extraction
text-embeddings-inference
Instructions to use nayan06/binary-classifier-conversion-intent-1.1-l12 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-l12 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("nayan06/binary-classifier-conversion-intent-1.1-l12") 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-l12 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("nayan06/binary-classifier-conversion-intent-1.1-l12") model = AutoModel.from_pretrained("nayan06/binary-classifier-conversion-intent-1.1-l12") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 97a26e993634dd85229ea68d2b61895e4c8c2f3a898e7b48bfd2f7ef375c6c2b
- Size of remote file:
- 4.05 kB
- SHA256:
- 212423d0d8f09eaaa2e7099733feb82720f077799abf852343471f9cd5db2dfd
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