Text Generation
PEFT
Safetensors
lora
rl
grpo
openenv
voice
indic
hindi
tamil
kannada
hinglish
schema-drift
gemma-3n
tool-use
conversational
Instructions to use DGXAI/gemma-3n-e2b-driftcall-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use DGXAI/gemma-3n-e2b-driftcall-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/gemma-3n-E2B-it") model = PeftModel.from_pretrained(base_model, "DGXAI/gemma-3n-e2b-driftcall-lora") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 75682b8f8a87592f12c6cce87c8ae26e8924e1b9c10ff90ac050c9f100c1f7d8
- Size of remote file:
- 4.7 MB
- SHA256:
- ea5f0cc48abfbfc04d14562270a32e02149a3e7035f368cc5a462786f4a59961
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.