Instructions to use AmelieSchreiber/esm2_t30_150M_ptm_qlora_2100K with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use AmelieSchreiber/esm2_t30_150M_ptm_qlora_2100K with PEFT:
from peft import PeftModel from transformers import AutoModelForTokenClassification base_model = AutoModelForTokenClassification.from_pretrained("facebook/esm2_t30_150M_UR50D") model = PeftModel.from_pretrained(base_model, "AmelieSchreiber/esm2_t30_150M_ptm_qlora_2100K") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7327ba860ba0c43e0cdee657f1a7749f1b44ebb6fdc4def4a0f6350f6fb038d1
- Size of remote file:
- 14.6 kB
- SHA256:
- 1bccfd6199f27e82b1e80be70b3d54ecbcf92e0aeadb5032e076fbabb66dc8d9
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