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
- Xet hash:
- e09257e99020416cdf06d15db401bf4cfa1a3afb4150b2bd48bc2cfb9dddb14d
- Size of remote file:
- 651 MB
- SHA256:
- 0c4b6632f3d3e73934d73476b17afe1f648c043f07add3536e332ec359ec723e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.