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:
- 7cd2d56b81002bf0d173aba9ee420b205e487fa9cf761e089a78fec422159759
- Size of remote file:
- 44.1 MB
- SHA256:
- b6435c1b0dd8eeb13a5972558d5101ca8313480a3bb903b000c1f3cf4d2d14f9
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