Instructions to use EleanorZzz/CMV_Llama-3.1-8B-Instruct_BC with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use EleanorZzz/CMV_Llama-3.1-8B-Instruct_BC 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, "EleanorZzz/CMV_Llama-3.1-8B-Instruct_BC") - Notebooks
- Google Colab
- Kaggle
Behavior Cloning Generator for Persuasive Argumentation
LoRA adapter fine-tuned on ChangeMyView data for persuasive argument generation.
Base Model
meta-llama/Llama-3.1-8B-Instruct
Training
Supervised fine-tuning (behavior cloning) on Delta-awarded CMV responses using LoRA.
Usage
from transformers import AutoModelForCausalLM, AutoTokenizer
from peft import PeftModel
base = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-3.1-8B-Instruct", device_map="auto")
model = PeftModel.from_pretrained(base, "EleanorZzz/CMV_Llama-3.1-8B-Instruct_BC")
tokenizer = AutoTokenizer.from_pretrained("EleanorZzz/CMV_Llama-3.1-8B-Instruct_BC")
Project
CS6120 Group 12 — Fine-tuning Language Models for Persuasive Argumentation
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Model tree for EleanorZzz/CMV_Llama-3.1-8B-Instruct_BC
Base model
meta-llama/Llama-3.1-8B Finetuned
meta-llama/Llama-3.1-8B-Instruct