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
File size: 361 Bytes
fa4d4d6 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | {
"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"
} |