Instructions to use malteos/scincl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use malteos/scincl with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("malteos/scincl") 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 malteos/scincl with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="malteos/scincl")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("malteos/scincl") model = AutoModel.from_pretrained("malteos/scincl") - Inference
- Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -1,7 +1,6 @@
|
|
| 1 |
---
|
| 2 |
pipeline_tag: sentence-similarity
|
| 3 |
tags:
|
| 4 |
-
- sentence-transformers
|
| 5 |
- feature-extraction
|
| 6 |
- sentence-similarity
|
| 7 |
language: en
|
|
|
|
| 1 |
---
|
| 2 |
pipeline_tag: sentence-similarity
|
| 3 |
tags:
|
|
|
|
| 4 |
- feature-extraction
|
| 5 |
- sentence-similarity
|
| 6 |
language: en
|