Sentence Similarity
Model2Vec
Safetensors
sentence-transformers
Turkish
embeddings
static-embeddings
Instructions to use atasoglu/1mb-turkish-embeddings with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Model2Vec
How to use atasoglu/1mb-turkish-embeddings with Model2Vec:
from model2vec import StaticModel model = StaticModel.from_pretrained("atasoglu/1mb-turkish-embeddings") embeddings = model.encode(["It's dangerous to go alone!", "It's a secret to everybody."]) print(embeddings.shape) - sentence-transformers
How to use atasoglu/1mb-turkish-embeddings with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("atasoglu/1mb-turkish-embeddings") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from atasoglu/1mb-turkish-embeddings: direct link, hf CLI and curl.
- Browser
- Download file 766 kB
-
https://huggingface.co/atasoglu/1mb-turkish-embeddings/resolve/main/tokenizer.json
- Command line
-
hf download hf://atasoglu/1mb-turkish-embeddings/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/atasoglu/1mb-turkish-embeddings/resolve/main/tokenizer.json
766 kB
File too large to display, you can check the raw version instead.