Instructions to use mrp/SCT_BERT_Tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use mrp/SCT_BERT_Tiny with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("mrp/SCT_BERT_Tiny") 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 mrp/SCT_BERT_Tiny with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mrp/SCT_BERT_Tiny", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:59c4c0d62addccef5521b946f0d196fb6b20817dd8b041b998b66a37576341f1
|
| 3 |
+
size 17552096
|