Text Generation
PEFT
Safetensors
age-verification
explanation
lora
qlora
multilingual
africa
conversational
Instructions to use Shinzmann/gemma-explain-lora-v0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Shinzmann/gemma-explain-lora-v0 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("google/gemma-4-E4B-it") model = PeftModel.from_pretrained(base_model, "Shinzmann/gemma-explain-lora-v0") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 90030e4762b7d35e8f89cfc6677c276f1c9c023bee0367f7d1131bfa8bf15f04
- Size of remote file:
- 5.78 kB
- SHA256:
- 1683343100ec3190f7fc08660595deef93918664092e8a0691f7d7d4cfff46b6
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