Transformers
PyTorch
t5
text2text-generation
protein-generation
sequence-generation
conditional-generation
text-generation-inference
Instructions to use MoMA-LAAS/prop2seq-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MoMA-LAAS/prop2seq-model with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("MoMA-LAAS/prop2seq-model") model = AutoModelForSeq2SeqLM.from_pretrained("MoMA-LAAS/prop2seq-model") - Notebooks
- Google Colab
- Kaggle
| { | |
| "mean": { | |
| "Rg": 14.92135140993968, | |
| "ete": 36.51412726240827, | |
| "scaling_exponent": 0.5339325049079684, | |
| "asphericity": 0.4559565227880063, | |
| "prefactor": 6.1388136438092085, | |
| "SHD": 2.5293296323763963, | |
| "FCR": 0.24488553975833108, | |
| "KL_hydropathy": -0.48035638511997825, | |
| "kappa*": -0.4252169368049604, | |
| "omega*": 0.0754381675942535, | |
| "SCD": 0.21557541074810355, | |
| "Length": 33.53519297326951, | |
| "Fract_pos": 0.12313853392284548, | |
| "Fract_neg": 0.12174700583548557, | |
| "NCPR": 0.001391528087359907 | |
| }, | |
| "std": { | |
| "Rg": 6.614851573439867, | |
| "ete": 15.422660980400911, | |
| "scaling_exponent": 0.0535883014001273, | |
| "asphericity": 0.03324832067125699, | |
| "prefactor": 0.6254380024980856, | |
| "SHD": 0.7088175174516826, | |
| "FCR": 0.10873439661879275, | |
| "KL_hydropathy": 0.810189166439004, | |
| "kappa*": 1.157971124069066, | |
| "omega*": 0.6659491393910585, | |
| "SCD": 1.5063322615485712, | |
| "Length": 26.25489301310707, | |
| "Fract_pos": 0.08248835096056287, | |
| "Fract_neg": 0.0898743042163313, | |
| "NCPR": 0.13394128637978803 | |
| } | |
| } |