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:
- a02f8f10e88b4196be95a26fdd7801aa00655388e6e122910a2dda93b0a33a90
- Size of remote file:
- 336 MB
- SHA256:
- 9d1c461118dd733cefc9b11f08ab71c5f163f08839e9ac789917f2944f57339e
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