Sentence Similarity
sentence-transformers
PyTorch
Safetensors
bloom
feature-extraction
mteb
Eval Results (legacy)
Instructions to use bigscience-data/sgpt-bloom-1b7-nli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use bigscience-data/sgpt-bloom-1b7-nli with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("bigscience-data/sgpt-bloom-1b7-nli") 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] - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#2
by SFconvertbot - opened
- .gitattributes +1 -0
- model.safetensors +3 -0
.gitattributes
CHANGED
|
@@ -27,3 +27,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
|
|
| 27 |
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
| 28 |
tokenizer.json filter=lfs diff=lfs merge=lfs -text
|
| 29 |
|
|
|
|
|
|
| 27 |
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
| 28 |
tokenizer.json filter=lfs diff=lfs merge=lfs -text
|
| 29 |
|
| 30 |
+
model.safetensors filter=lfs diff=lfs merge=lfs -text
|
model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:0d5e02ccc87c78a317b2a1f3026ce3cf2e45ca1b225faa51847eeb927df96a18
|
| 3 |
+
size 6889666656
|