Instructions to use AmelieSchreiber/esm2_t12_35M_lora_binding_sites_cp2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use AmelieSchreiber/esm2_t12_35M_lora_binding_sites_cp2 with PEFT:
from peft import PeftModel from transformers import AutoModelForTokenClassification base_model = AutoModelForTokenClassification.from_pretrained("facebook/esm2_t12_35M_UR50D") model = PeftModel.from_pretrained(base_model, "AmelieSchreiber/esm2_t12_35M_lora_binding_sites_cp2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9ff7dd38364e20eb1e9313aa3804deceb3ea006fa94eb60e01ffb7f15f66d5b8
- Size of remote file:
- 14.6 kB
- SHA256:
- 7b0e7343e53950faee5bbd21ff23f65d19afc16fea38b3587c0fa23b173f0a4d
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