Sentence Similarity
sentence-transformers
PyTorch
Transformers
bert
feature-extraction
text-embeddings-inference
Instructions to use rithwik-db/docs_model_v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use rithwik-db/docs_model_v1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("rithwik-db/docs_model_v1") 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 rithwik-db/docs_model_v1 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("rithwik-db/docs_model_v1") model = AutoModel.from_pretrained("rithwik-db/docs_model_v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 04ae95716c2c7102bc723a435a9c72bf2762d7a15828d754562f7302113d841f
- Size of remote file:
- 1.34 GB
- SHA256:
- 64b585524c2bab768f7e57c9a9a4dd60f4d15dc0b430121f3133ccc01e5cdeb2
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