model_creator, quantized_by, model_name, pretty_name, model_type, prompt_template, base_model, library_name, license, datasets, language, pipeline_tag, task_categories, inference, widget, tags, model-index

model_creator	quantized_by	model_name	pretty_name	model_type	prompt_template	base_model	library_name	license	datasets	language	pipeline_tag	task_categories	inference	widget	tags	model-index
Nekochu	Nekochu	Luminia 13B v3	Luminia	llama2	Below is an instruction that describes a task. Write a response that appropriately completes the request. ### Instruction: {Instruction} {summary} ### input: {category} ### Response: {prompt}	meta-llama/Llama-2-13b-chat-hf	peft	apache-2.0	Nekochu/discord-unstable-diffusion-SD-prompts glaiveai/glaive-function-calling-v2 TIGER-Lab/MathInstruct Open-Orca/SlimOrca GAIR/lima sahil2801/CodeAlpaca-20k garage-bAInd/Open-Platypus	en	text-generation	question-answering text2text-generation conversational	True	example_title messages output prompt assistant role content system Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request. role content user ### Instruction: Create stable diffusion metadata based on the given english description. Luminia ### Input: favorites and popular SFW ### Response: text Luminia, 1girl, solo, blonde hair, long hair,	llama-factory lora generated_from_trainer llama2 llama instruct finetune gpt4 synthetic data stable diffusion alpaca llm	name results Luminia-13B-v3

Luminia v3 is good at reasoning to enhance Stable Diffusion prompt from short summary description, may output NSFW content.

LoRa is include and Quants: exllamav2 2.4bpw-h6, 4.25bpw-h6, 8.0bpw-h8 | GGUF Q4_K_M, IQ4_NL |

Prompt template: Alpaca

Output example tested In text-generation-webui

Input	base llama-2-chat	QLoRa
[question]: Create stable diffusion metadata based on the given english description. Luminia \n### Input:\n favorites and popular SFW	Answer: Luminia, a mystical world of wonder and magic 🧝‍♀️✨ A place where technology and nature seamlessly blend together ...	Answer! < lora:Luminari-10:0.8> Luminari, 1girl, solo, blonde hair, long hair, blue eyes, (black dress), looking at viewer, night sky, starry sky, constellation, smile, upper body, outdoors, forest, moon, tree, mountain, light particle ....

Output prompt from QLoRa to A1111/SD-WebUI:

Full Prompt

Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.

### Instruction:
Create stable diffusion metadata based on the given english description. Luminia

### Input:
favorites and popular SFW

### Response:

"Luminia" can be any short description, more info on my SD dataset here.

Training Details

Click to see details

Model Description

• Train by: Nekochu, Model type: Llama, Finetuned from model Llama-2-13b-chat

• Continue from the base of LoRA Luminia-13B-v2-QLora

  Know issue: [issue]

Trainer

• hiyouga/LLaMA-Efficient-Tuning

  Hardware: QLoRA training OS Windows, Python 3.10.8, CUDA 12.1 on 24GB VRAM.

Training hyperparameters

The following hyperparameters were used during training:

• num_epochs: 1.0
• finetuning_type: lora
• quantization_bit: 4
• stage: sft
• learning_rate: 5e-05
• cutoff_len: 4096
• num_train_epochs: 3.0
• max_samples: 100000
• warmup_steps: 0
• train_batch_size: 1
• distributed_type: single-GPU
• num_devices: 1
• warmup_steps: 0
• rope_scaling: linear
• lora_rank: 32
• lora_target: all
• lora_dropout: 0.15
• bnb_4bit_compute_dtype: bfloat16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine

training_loss:

Framework versions

• PEFT 0.9.0
• Transformers 4.38.1
• Pytorch 2.1.2+cu121
• Datasets 2.14.5
• Tokenizers 0.15.0