Sentence Similarity
Transformers
PyTorch
bert
feature-extraction
text2vec
mteb
Eval Results (legacy)
text-embeddings-inference
Instructions to use barisaydin/text2vec-base-multilingual with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use barisaydin/text2vec-base-multilingual with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("barisaydin/text2vec-base-multilingual") model = AutoModel.from_pretrained("barisaydin/text2vec-base-multilingual", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download .DS_Store from barisaydin/text2vec-base-multilingual: direct link, hf CLI and curl.
- Browser
- Download file 6.15 kB
-
https://huggingface.co/barisaydin/text2vec-base-multilingual/resolve/main/.DS_Store
- Command line
-
hf download hf://barisaydin/text2vec-base-multilingual/.DS_Store
-
curl -L -o .DS_Store https://huggingface.co/barisaydin/text2vec-base-multilingual/resolve/main/.DS_Store
6.15 kB
This file contains binary data. It cannot be displayed, but you can still download it.