Sentence Similarity
sentence-transformers
PyTorch
Transformers
Indonesian
bert
feature-extraction
text-embeddings-inference
Instructions to use cassador/indobert-embeddings with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use cassador/indobert-embeddings with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("cassador/indobert-embeddings") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Transformers
How to use cassador/indobert-embeddings with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("cassador/indobert-embeddings") model = AutoModel.from_pretrained("cassador/indobert-embeddings", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -131,4 +131,6 @@ SentenceTransformer(
|
|
| 131 |
|
| 132 |
## Citing & Authors
|
| 133 |
|
| 134 |
-
<!--- Describe where people can find more information -->
|
|
|
|
|
|
|
|
|
| 131 |
|
| 132 |
## Citing & Authors
|
| 133 |
|
| 134 |
+
<!--- Describe where people can find more information -->
|
| 135 |
+
This Model authored by:
|
| 136 |
+
https://huggingface.co/rahmanfadhil/indobert-finetuned-indonli
|