Sentence Similarity
sentence-transformers
Safetensors
xlm-roberta
feature-extraction
text-embeddings-inference
Instructions to use JaehyeokLee/preliminary_random_infonce_checkpoint_epoch_1_step_100 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use JaehyeokLee/preliminary_random_infonce_checkpoint_epoch_1_step_100 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("JaehyeokLee/preliminary_random_infonce_checkpoint_epoch_1_step_100") 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] - Notebooks
- Google Colab
- Kaggle
File size: 54 Bytes
65c0217 | 1 2 3 4 | {
"max_seq_length": 1024,
"do_lower_case": false
} |