Feature Extraction
sentence-transformers
Safetensors
sentence-similarity
biomedical
embeddings
life-sciences
scientific-text
SODA-VEC
EMBO
Instructions to use EMBO/vicreg_exact with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use EMBO/vicreg_exact with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("EMBO/vicreg_exact") 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] - Notebooks
- Google Colab
- Kaggle
Training in progress, step 10000
Browse files- model.safetensors +1 -1
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 596070136
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:6e94b033abf60f58dabc61c2bf4d8f31a8e551c1813dcdecfd8c569353ea288e
|
| 3 |
size 596070136
|