Feature Extraction
sentence-transformers
Safetensors
modernbert
sentence-similarity
biomedical
embeddings
life-sciences
scientific-text
SODA-VEC
EMBO
text-embeddings-inference
Instructions to use EMBO/vicreg_our_contrast with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use EMBO/vicreg_our_contrast with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("EMBO/vicreg_our_contrast") 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 5000
Browse files- model.safetensors +1 -1
- training_args.bin +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:c8691bb7510f92adc7c4e8df9b09395055833fbd7aabd7f96847eaec8add576f
|
| 3 |
size 596070136
|
training_args.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 6072
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:17bc91ddf71728158784505af88497985de1ee891f2d7b43ee34740ea37fa7f7
|
| 3 |
size 6072
|