Sentence Similarity
Transformers
PyTorch
English
deberta-v2
feature-extraction
PubChem
chemistry
biology
deberta-v3
text-embeddings-inference
Instructions to use mschuh/PubChemDeBERTa-augmented with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mschuh/PubChemDeBERTa-augmented with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("mschuh/PubChemDeBERTa-augmented") model = AutoModel.from_pretrained("mschuh/PubChemDeBERTa-augmented", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f83f006a973652c805d268df7ea8f92b7197197fea9e4c19c35b53ce837a8b25
- Size of remote file:
- 735 MB
- SHA256:
- 5a942f37626efa4aaf480df90b13042b9cba3a08fe43a1c25ce510fa934cd4d8
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