Sentence Similarity
Transformers
PyTorch
TensorFlow
JAX
Safetensors
bert
feature-extraction
sentence_embedding
multilingual
google
text-embeddings-inference
Instructions to use setu4993/LaBSE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use setu4993/LaBSE with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("setu4993/LaBSE") model = AutoModel.from_pretrained("setu4993/LaBSE", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Update config.json
#1
by supreet-kore - opened
Adding labels for zeroshot classification pipeline
@supreet-kore : Thank you for opening this PR. I'm curious about a few things before I feel comfortable merging this:
- How was the label set determined + created?
- AFAIK, LaBSE was not trained on NLI, so curious why we'd want it to be used with zero-shot pipelines for NLI with NLI labels?
- I haven't followed along on some of the recent updates. Can you please point me to documentation that describes this syntax?
Appreciate your contribution, just hoping to get a bit more clarity before merging this. Thanks.
setu4993 changed pull request status to closed