Transformers
PyTorch
bart
text2text-generation
molecular language model
SELFIES
molecule optimization
Instructions to use zjunlp/MolGen-large-opt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zjunlp/MolGen-large-opt with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("zjunlp/MolGen-large-opt") model = AutoModelForSeq2SeqLM.from_pretrained("zjunlp/MolGen-large-opt") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 71796df5f7730512086b0660a38782ee66883f5217fda7499f42ddea01641209
- Size of remote file:
- 1.42 GB
- SHA256:
- db03cd3cd6a8c8ca3becf82f5ea15c2e37027cf829bb4b4580d2766df12a168a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.