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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 93c60cc96f96a62dc0d25de9c21fdb0e9fe01c29ebf378f56d1097bd24a769ca
- Size of remote file:
- 90.9 MB
- SHA256:
- bfbefda7b77f0ff43f6587eba0f23e7220575196f33a78ba3153175deb3e7c70
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