Sentence Similarity
Transformers
PyTorch
Chinese
bert
feature-extraction
PEG
mteb
Eval Results (legacy)
text-embeddings-inference
Instructions to use TownsWu/PEG with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TownsWu/PEG with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("TownsWu/PEG") model = AutoModel.from_pretrained("TownsWu/PEG") - Notebooks
- Google Colab
- Kaggle
Ablations with InfoNCE
#5
by tomaarsen - opened
Hello!
I'm quite interested in your work - I think progressively shifting the focus of the learning is quite smart. I was wondering if you performed any ablations against just InfoNCE? It's a bit hard to know whether your loss function actually outperforms InfoNCE, or if the gains are e.g. just from using better datasets.
- Tom Aarsen
Same concern