Instructions to use Maxenith/MAXENITH-40B-LoRA-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Maxenith/MAXENITH-40B-LoRA-v2 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Maxenith/MAXENITH-32B") model = PeftModel.from_pretrained(base_model, "Maxenith/MAXENITH-40B-LoRA-v2") - Notebooks
- Google Colab
- Kaggle
MAXENITH-40B-LoRA-v2
LoRA adapter for a block-expanded Maxenith/MAXENITH-32B (64 -> 80 layers: a copy of every 4th layer is inserted right after it, with o_proj/down_proj zeroed). LoRA trains only the 16 new layers (indices 4, 9, ..., 79). Data: SmolKalam (Arabic), OpenThoughts-114k, OpenCodeReasoning, NuminaMath-CoT, MetaMathQA, Magicoder.
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Base model
Maxenith/MAXENITH-32B