Instructions to use DavidBShan/tinker-lora5-71be4554-llama31-8b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use DavidBShan/tinker-lora5-71be4554-llama31-8b with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-3.1-8B-Instruct") model = PeftModel.from_pretrained(base_model, "DavidBShan/tinker-lora5-71be4554-llama31-8b") - Notebooks
- Google Colab
- Kaggle
DavidBShan/tinker-lora5-71be4554-llama31-8b
This model was fine-tuned from meta-llama/Llama-3.1-8B-Instruct using Tinker and tinker-cookbook.
Model details
- Base model: meta-llama/Llama-3.1-8B-Instruct
- Format: LoRA adapter (PEFT)
Usage
from peft import PeftModel
from transformers import AutoModelForCausalLM
base = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-3.1-8B-Instruct")
model = PeftModel.from_pretrained(base, "DavidBShan/tinker-lora5-71be4554-llama31-8b")
Framework versions
- tinker-cookbook: 0.4.0
- transformers: 5.5.3
- torch: 2.12.0+cpu
- Downloads last month
- 15
Model tree for DavidBShan/tinker-lora5-71be4554-llama31-8b
Base model
meta-llama/Llama-3.1-8B Finetuned
meta-llama/Llama-3.1-8B-Instruct