Text Generation
PEFT
Safetensors
lora
fine-tuning
language-model
code-generation
natural-language-understanding
mathematical-reasoning
safety-alignment
multi-task
continual-learning
llama
llama-3
Instructions to use juzhengz/LoRI-D_code_llama3_rank_32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use juzhengz/LoRI-D_code_llama3_rank_32 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Meta-Llama-3-8B") model = PeftModel.from_pretrained(base_model, "juzhengz/LoRI-D_code_llama3_rank_32") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4bdd353a7b8aa58f0f6e7718f641d15ba85790d47d4f01a41771a084b87995c7
- Size of remote file:
- 44.1 MB
- SHA256:
- 50e4253036a4224869502a8da45bf568dd44c4124b79520a63e6b8e746d8f7ed
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.