Instructions to use AmelieSchreiber/esm2_t12_35M_LoRA_RNA_binding with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use AmelieSchreiber/esm2_t12_35M_LoRA_RNA_binding 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_RNA_binding") - Transformers
How to use AmelieSchreiber/esm2_t12_35M_LoRA_RNA_binding with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("AmelieSchreiber/esm2_t12_35M_LoRA_RNA_binding", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d2c053884812103b7dc798f014d9b4fc4108e990b02acb2b2eff531a0226a2e0
- Size of remote file:
- 2.53 MB
- SHA256:
- 59da0abe4a1c0143017d0040141e71de0707ba17a03aecd6035ee6f887e5c6ff
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