Sentence Similarity
sentence-transformers
PyTorch
TensorBoard
Safetensors
Transformers
bert
feature-extraction
text-embeddings-inference
Instructions to use srsawant34/ProTopic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use srsawant34/ProTopic with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("srsawant34/ProTopic") 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 srsawant34/ProTopic with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("srsawant34/ProTopic") model = AutoModel.from_pretrained("srsawant34/ProTopic") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5bbd7cdce9552cedb975d4101ef357cedab0f503bf9e1a7843906501da6d8ba5
- Size of remote file:
- 90.9 MB
- SHA256:
- 77c443b12403ef20b443a28ab555a1f702b73c04d5b86894ac5fd59f049eed61
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