Fill-Mask
Transformers
PyTorch
Safetensors
code
bert
chemistry
selfies
drug-discovery
herbal
coconutdb
chembl34
drugs
molecules
compounds
ranger21
madgrad
Eval Results (legacy)
Instructions to use gbyuvd/chemselfies-base-bertmlm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gbyuvd/chemselfies-base-bertmlm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="gbyuvd/chemselfies-base-bertmlm")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("gbyuvd/chemselfies-base-bertmlm") model = AutoModelForMaskedLM.from_pretrained("gbyuvd/chemselfies-base-bertmlm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0415dd8e937d1ad0c87f826923742986b4b0034ddc9e4b8e326078f237be0114
- Size of remote file:
- 44.6 MB
- SHA256:
- 7ecddd24834ca750b4bbd01452bee86627548c56c9bdeb7632f7e46ab21be2a6
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.