How to use from
Unsloth Studio
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for impactframes/IF_AI_SD_PromptMkr to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for impactframes/IF_AI_SD_PromptMkr to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for impactframes/IF_AI_SD_PromptMkr to start chatting
Load model with FastModel
pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
    model_name="impactframes/IF_AI_SD_PromptMkr",
    max_seq_length=2048,
)
Quick Links

LLaMA3 License and Usage

Model Visualization

Introduction

The LLaMA3 model is equipped to deliver superior results in machine learning applications. This model is particularly effective when used in conjunction with the IF_AI_tools custom node for ComfyUI and the IF_PromptMKr, my extension for A1111 Forge and Next platforms.

Model Training

LLaMA3 has been meticulously trained on a synthetic dataset comprising over 50,000 high-quality, stable diffusion prompts, ensuring robustness and high performance across various tasks.

Useful Links

Support

Your support is invaluable in continuing the development and enhancement of tools like these. If you find this tool useful, please consider extending your support by:

Thank you for your interest and support!

  • Developed by: impactframes
  • License: apache-2.0
  • Finetuned from model : unsloth/llama-3-8b-bnb-4bit

This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.

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