Fill-Mask
Transformers
PyTorch
English
roberta
smart-contract
web3
software-engineering
embedding
codebert
Instructions to use web3se/SmartBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use web3se/SmartBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="web3se/SmartBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("web3se/SmartBERT") model = AutoModelForMaskedLM.from_pretrained("web3se/SmartBERT") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a572c2fd803203823425aba2189cff29e8f62c405df0abb04a2ed9ccf124b7be
- Size of remote file:
- 4.03 kB
- SHA256:
- 9b0da450342b037e604e0cf49e4db05d8c1bf2a6735c6da8cce707f438b68765
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.