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llamabase-r-16 – AI Model by kevin009 | AlphaNeural AI

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kevin009/
llamabase-r-16

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Model Overview

A LoRA (Low-Rank Adaptation) decomposed from base model from base to instruct

Model Details

Base Model: (meta-llama/Llama-3.1-8B) - (meta-llama/Llama-3.1-8B-instruct)
Adaptation Method: LoRA

Training Configuration

Training Hyperparameters

Rank (r): 16 -> 16
Alpha: 1 -> 16

LoRA Configuration

Rank (r): 16
Alpha: 16
Target Modules:
- q_proj (Query projection)
- k_proj (Key projection)
- v_proj (Value projection)
- o_proj (Output projection)
- up_proj (Upsampling projection)
- down_proj (Downsampling projection)
- gate_proj (Gate projection)

Usage

This adapter must be used in conjunction with the base Llama-3.1-8B-instruct model.

Loading the Model

python

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

# Load base model
base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-3.1-8B-instruct")
tokenizer = AutoTokenizer.from_pretrained("meta-llama/Llama-3.1-8B-instruct")

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

Limitations and Biases

This adapter might inherits some limitations and biases present in the base Llama-3.1-8B-instruct model