Sentence Similarity
sentence-transformers
PyTorch
Transformers
bert
feature-extraction
text-embeddings-inference
Instructions to use nayan06/binary-classifier-conversion-intent-1.1-l6 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-l6 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("nayan06/binary-classifier-conversion-intent-1.1-l6") 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-l6 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("nayan06/binary-classifier-conversion-intent-1.1-l6") model = AutoModel.from_pretrained("nayan06/binary-classifier-conversion-intent-1.1-l6") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 94a3b46ce693796c1476a67f2169315596d25e2973d0aad1283c022652474305
- Size of remote file:
- 4.05 kB
- SHA256:
- 34913550605fc4e3f3999e79944977644ab9d3dcbd462a2de849f01ac0d9e70b
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