Instructions to use ChatterjeeLab/PepMLM-650M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ChatterjeeLab/PepMLM-650M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="ChatterjeeLab/PepMLM-650M")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("ChatterjeeLab/PepMLM-650M") model = AutoModelForMaskedLM.from_pretrained("ChatterjeeLab/PepMLM-650M") - Inference
- Notebooks
- Google Colab
- Kaggle
| { | |
| "cls_token": "<cls>", | |
| "eos_token": "<eos>", | |
| "mask_token": "<mask>", | |
| "pad_token": "<pad>", | |
| "unk_token": "<unk>" | |
| } | |