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:
- c90e3055e4c0658c398d242dbfca86ba87cfb34c8084314469d96f8b0510b491
- Size of remote file:
- 14.6 kB
- SHA256:
- 7620e37bc2e6da54aa1e68fd5cb88e282fc51b57b496e91af2baf81c3d787e0c
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