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
I'm receiving an error Non-consecutive added token '[PAD]' found
#6 opened about 2 years ago
by
Koat
Add transformers.js tag
#5 opened over 2 years ago
by
do-me
Do you have guide to convert this to GGUF/GGML format?
1
#4 opened over 2 years ago
by
qhkm
Any guidance on how to use this with sentence-transformers without downloading a bunch of extra stuff?
5
#3 opened over 2 years ago
by
simonw
Very cool!
❤️ 2
1
#1 opened over 2 years ago
by
clem