Sentence Similarity
sentence-transformers
PyTorch
ONNX
Safetensors
Transformers
bert
feature-extraction
mteb
Eval Results (legacy)
text-embeddings-inference
Instructions to use TaylorAI/gte-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use TaylorAI/gte-tiny with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("TaylorAI/gte-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 TaylorAI/gte-tiny with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("TaylorAI/gte-tiny") model = AutoModel.from_pretrained("TaylorAI/gte-tiny") - Inference
- Notebooks
- Google Colab
- Kaggle
Commit ·
6d24d7a
1
Parent(s): ab639c4
Adding `safetensors` variant of this model (#2)
Browse files- Adding `safetensors` variant of this model (f0900ddec0ae4f706ebd554c710dd2396d110936)
Co-authored-by: Radamés Ajna <radames@users.noreply.huggingface.co>
- model.safetensors +3 -0
model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:41282c37ddd19dbf7352fca3bafd3d187baffacd7231f3f0cd69b7525630e08d
|
| 3 |
+
size 45457576
|