Instructions to use rohitnagareddy/gemma-2b-python-expert-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use rohitnagareddy/gemma-2b-python-expert-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("google/gemma-2b-it") model = PeftModel.from_pretrained(base_model, "rohitnagareddy/gemma-2b-python-expert-lora") - Notebooks
- Google Colab
- Kaggle
| { | |
| "base_model_name_or_path": "google/gemma-2b-it", | |
| "peft_type": "LORA", | |
| "task_type": "CAUSAL_LM", | |
| "r": 16, | |
| "lora_alpha": 32, | |
| "lora_dropout": 0.1, | |
| "target_modules": [ | |
| "q_proj", | |
| "k_proj", | |
| "v_proj", | |
| "o_proj", | |
| "gate_proj", | |
| "up_proj", | |
| "down_proj" | |
| ], | |
| "inference_mode": false, | |
| "fan_in_fan_out": false, | |
| "bias": "none" | |
| } |