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:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("TaylorAI/gte-tiny") model = AutoModel.from_pretrained("TaylorAI/gte-tiny", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from TaylorAI/gte-tiny: direct link, hf CLI and curl.
- Browser
- Download file 45.5 MB
-
https://huggingface.co/TaylorAI/gte-tiny/resolve/bc7cbe829d6fcaaf31094f9ac4fac607e0c45683/pytorch_model.bin
- Command line
-
hf download hf://TaylorAI/gte-tiny@bc7cbe829d6fcaaf31094f9ac4fac607e0c45683/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/TaylorAI/gte-tiny/resolve/bc7cbe829d6fcaaf31094f9ac4fac607e0c45683/pytorch_model.bin
45.5 MB
- Xet hash:
- 8557a4129b2aa16d59f4891ec318d2d9cd2b51d93c5394f401ef5871b3abbd98
- Size of remote file:
- 45.5 MB
- SHA256:
- 4b4288c1825166bed706aeba0442bc949bf1e1a8294e61dd4531e6a2dcadd471
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