grimulkan/LimaRP-augmented
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How to use mpasila/Llama-3-Instruct-LiPPA-LoRA-8B with PEFT:
from peft import PeftModel
from transformers import AutoModelForCausalLM
base_model = AutoModelForCausalLM.from_pretrained("unsloth/llama-3-8b-Instruct-bnb-4bit")
model = PeftModel.from_pretrained(base_model, "mpasila/Llama-3-Instruct-LiPPA-LoRA-8B")How to use mpasila/Llama-3-Instruct-LiPPA-LoRA-8B with Transformers:
# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("mpasila/Llama-3-Instruct-LiPPA-LoRA-8B", device_map="auto")LoRA trained in 4-bit with 8k context using meta-llama/Meta-Llama-3-8B-Instruct as the base model for 1 epoch.
Dataset used is mpasila/LimaRP-PIPPA-Mix-8K-Context which was made using grimulkan/LimaRP-augmented and KaraKaraWitch/PIPPA-ShareGPT-formatted.
This has been trained on the instruct model and not the base model. The model trained with the base model using the same dataset is here: mpasila/Llama-3-LiPPA-LoRA-8B
Unsloth changed assistant to gpt and user to human.
This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.
Base model
unsloth/llama-3-8b-Instruct-bnb-4bit