Sentence Similarity
sentence-transformers
PyTorch
Safetensors
Transformers
mpnet
feature-extraction
text-embeddings-inference
Instructions to use Collab-uniba/github-issues-mpnet-st-e10 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Collab-uniba/github-issues-mpnet-st-e10 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Collab-uniba/github-issues-mpnet-st-e10") 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 Collab-uniba/github-issues-mpnet-st-e10 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Collab-uniba/github-issues-mpnet-st-e10") model = AutoModel.from_pretrained("Collab-uniba/github-issues-mpnet-st-e10") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -8,7 +8,7 @@ tags:
|
|
| 8 |
|
| 9 |
---
|
| 10 |
|
| 11 |
-
#
|
| 12 |
|
| 13 |
This is a [sentence-transformers](https://www.SBERT.net) model, specific for GitHub Issue data.
|
| 14 |
|
|
|
|
| 8 |
|
| 9 |
---
|
| 10 |
|
| 11 |
+
# GitHub Issues MPNet Sentence Transformer (10 Epochs)
|
| 12 |
|
| 13 |
This is a [sentence-transformers](https://www.SBERT.net) model, specific for GitHub Issue data.
|
| 14 |
|