Instructions to use PJMixers-Dev/google_gemma-3-4b-it-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use PJMixers-Dev/google_gemma-3-4b-it-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("google/gemma-3-4b-pt") model = PeftModel.from_pretrained(base_model, "PJMixers-Dev/google_gemma-3-4b-it-lora") - Notebooks
- Google Colab
- Kaggle
| { | |
| "base_model_name_or_path": "google/gemma-3-4b-pt", | |
| "peft_type": "LORA", | |
| "use_rslora": false, | |
| "target_modules": "model\\.language_model\\.layers\\.[\\d]+.(mlp|cross_attn|self_attn).(up|down|gate|q|k|v|o)_proj", | |
| "modules_to_save": [], | |
| "task_type": "CAUSAL_LM", | |
| "r": 64, | |
| "lora_alpha": 64, | |
| "rank_pattern": {}, | |
| "alpha_pattern": {}, | |
| "lora_dropout": 0.0, | |
| "fan_in_fan_out": false, | |
| "inference_mode": true | |
| } |