Instructions to use AmelieSchreiber/esm2_t12_35M_qlora_binding_sites_v0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use AmelieSchreiber/esm2_t12_35M_qlora_binding_sites_v0 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_qlora_binding_sites_v0") - Notebooks
- Google Colab
- Kaggle
| { | |
| "alpha_pattern": {}, | |
| "auto_mapping": null, | |
| "base_model_name_or_path": "facebook/esm2_t12_35M_UR50D", | |
| "bias": "none", | |
| "fan_in_fan_out": false, | |
| "inference_mode": true, | |
| "init_lora_weights": true, | |
| "layers_pattern": null, | |
| "layers_to_transform": null, | |
| "lora_alpha": 1, | |
| "lora_dropout": 0.5, | |
| "modules_to_save": [ | |
| "classifier" | |
| ], | |
| "peft_type": "LORA", | |
| "r": 2, | |
| "rank_pattern": {}, | |
| "revision": null, | |
| "target_modules": [ | |
| "query", | |
| "key", | |
| "value", | |
| "dense" | |
| ], | |
| "task_type": "TOKEN_CLS" | |
| } |