metadata
library_name: transformers
tags: []
Model Card for Meta-Llama3-8B-Instruct-assessment
Model Details
Model Description
This is the model card of a Meta-Llama3-8B-Instruct-assessment model that has been developed by fine-tuning Meta-Llama3-8B-Instruct. The model is finetuned using LoRA and the model was loaded in 16bit. Low-Rank Adaptation, also known as LoRA, makes fine-tuning LLMs easier by reducing the number of trainable parameters to produce lightweight and efficient models. LoRA was utilized by modifying matrix rank 'r' and alpha values.
- Developed by: xap
- License: llama3
- Finetuned from model : meta-llama/Meta-Llama-3-8B-Instruct
- Finetuned using dataset : SelfCode2.0
How to Get Started with the Model
The dataset or input for this model should be in the alpaca format.
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("xap/Meta-Llama3-8B-Instruct-assessment")
base_model = AutoModelForCausalLM.from_pretrained("xap/Meta-Llama3-8B-Instruct-assessment")
lora_config = LoraConfig.from_pretrained("xap/Meta-Llama3-8B-Instruct-assessment")
model = PeftModel.from_pretrained(
base_model,
"xap/Meta-Llama3-8B-Instruct-assessment",
lora_config=lora_config,
)