Sentence Similarity
Transformers
PyTorch
Safetensors
xlm-roberta
feature-extraction
mteb
Eval Results (legacy)
text-embeddings-inference
Instructions to use deepfile/embedder-100p with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deepfile/embedder-100p with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("deepfile/embedder-100p") model = AutoModel.from_pretrained("deepfile/embedder-100p") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dbd4a649f75eff8f33922cee855d7bc2d2417d0fbb3053f72437f079ef3af5b2
- Size of remote file:
- 17.1 MB
- SHA256:
- 728547bab925e8c1b7be400b0ea09701f0b6936424c6ed415cb67a280668b618
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.