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:
- d13f97c9b698ee4eef3908da1fa201a5cf78683484518f697691b5f37c3cd7bf
- Size of remote file:
- 307 kB
- SHA256:
- a01f9ab0c7791ac8d9408740883f1b3267a15696f32e2bf1693bb76687206976
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