Sentence Similarity
sentence-transformers
Transformers
xlm-roberta
feature-extraction
text-embeddings-inference
Instructions to use ramdane/Juri with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use ramdane/Juri with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("ramdane/Juri") 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 ramdane/Juri with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("ramdane/Juri") model = AutoModel.from_pretrained("ramdane/Juri", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Upload config.json
80fe566 -
Create 1_Pooling/f.txt
d19706f -
Delete 1_Pooling
29cfeb4 -
Create 1_Pooling/
29d62a1 -
Delete 1_Pooling
c7ba2e7 -
Delete .gitattributes
16db6d5 -
Update 1_Pooling/config.json
170fd19 -
Create 1_Pooling/config.json
6518c73 -
Upload 10 files
c189626
-
initial commit
7b35418