Instructions to use AmelieSchreiber/esm2_t12_35M_ptm_qlora_2100K with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use AmelieSchreiber/esm2_t12_35M_ptm_qlora_2100K 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_ptm_qlora_2100K") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ab35ebe7a97d16709e3ec3d5e6c9d50050c3a5d54055f525b944c6e286e9d92d
- Size of remote file:
- 613 kB
- SHA256:
- 5ece97dd78a3f8a055c6517446f92c836c43ed4c033cd2be90739e4f7dca4e8e
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