ndavidson/phi-3.1-preference

LoRA Adapter for [Base Model Name]

This is a LoRA adapter trained on [describe your training data and task].

Usage

To use this adapter:

from peft import PeftModel, PeftConfig
from transformers import AutoModelForCausalLM, AutoTokenizer

base_model_name = "base_model_name"
adapter_name = "your-username/your-lora-adapter-name"

# Load base model
base_model = AutoModelForCausalLM.from_pretrained(base_model_name)
tokenizer = AutoTokenizer.from_pretrained(base_model_name)

# Load LoRA adapter
model = PeftModel.from_pretrained(base_model, adapter_name)

# Use the model
input_text = "Your input text here"
inputs = tokenizer(input_text, return_tensors="pt")
outputs = model.generate(**inputs)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))