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:
- c9d70afd3bbcd2a887fa7990eed99333c2839b5bc9ff9160d7ae1e2a436202ad
- Size of remote file:
- 623 kB
- SHA256:
- 05261168043270dab3324841624c1620dece04af673dd3bd900152c21cc5a274
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