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How to use x0root/Llama-3.1-8B-Orca-Structured-LoRA with PEFT:
from peft import PeftModel
from transformers import AutoModelForCausalLM
base_model = AutoModelForCausalLM.from_pretrained("unsloth/Meta-Llama-3.1-8B-Instruct-bnb-4bit")
model = PeftModel.from_pretrained(base_model, "x0root/Llama-3.1-8B-Orca-Structured-LoRA")How to use x0root/Llama-3.1-8B-Orca-Structured-LoRA with Unsloth Studio:
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for x0root/Llama-3.1-8B-Orca-Structured-LoRA to start chatting
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for x0root/Llama-3.1-8B-Orca-Structured-LoRA to start chatting
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for x0root/Llama-3.1-8B-Orca-Structured-LoRA to start chatting
pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
model_name="x0root/Llama-3.1-8B-Orca-Structured-LoRA",
max_seq_length=2048,
)