Nekochu

.spoiler{background:black;color:black;text-decoration:none!important}.spoiler a{color:black;text-decoration:underline}.spoiler:hover,.spoiler:hover a{color:white} You can use this model in stable-audio-tools, fine-tuned on my favorite song from my personal playlist. Feel-Good Vibes and Dramatic Atmosphere, alone hero, epic, get good yeah, better last night pop, follow follow, echoing, powerful vocal driving melancholic vocals dramatic Features rising tension, progressive electro house, far away, by Alan Walker, popular song tempo, girl, female synth, popular, titled: legend never die Beautiful music progressive electro slap mood, upbeat, heavy bass, melancholic, hopeful; drums, vocals, dynamic shifts, building intensity, run far away, repetitive, let let go, think of us, titled popular lyrics: Mirror's Edge, popular lyrics say: "still still alive" Chill soft wake up, slow down alt, night get lucky dance, relax music introspective 2017 2018 2019 2020 2021 2022, acoustic atmosphere uplifting dreams, dreamy indie pop, electric trap, percussion, higher reverb, really intensity melody, goodbye Chill hip-hop beat, chillhop, lofi pop, favorite music Prompt have been chosen based on the top tagged words except last prompt which is used to compare effect on non-trained tags ### Dataset: 2-3 min music length - All of my Liked music download and auto label so mostly copyright. - Total number of samples: ~1383 - `"randomcrop": true` in datasetconfig.json ### Settings: - Training epochs: 1 - Training steps: 1383 - Learning rate: 1e-05

Model created by Nekochu, quantized by Nekochu.

Model created by Nekochu, quantized by Nekochu.

This model is based on the Meta Llama 3.1 8B Instruct and is licensed under Apache 2.0. It utilizes the PEFT library.

from transformers import AutoModelForSeq2SeqLM , AutoTokenizer model = AutoModelForSeq2SeqLM . frompretrained ( "Nekochu/myt5-large-SD-prompts" , devicemap = "auto" ) tokenizer = AutoTokenizer . frompretrained ( "Nekochu/myt5-large-SD-prompts" ) prompt = "### Instruction:\nCreate stable diffusion metadata based on the given english description. a futuristic city\n\n### Response:\n" inputs = tokenizer ( prompt , returntensors = "pt" , maxlength = 256 , truncation = True ). to ( model . device ) outputs = model . generate ( inputs , maxlength = 256 , numbeams = 5 , earlystopping = True ) result = tokenizer . decode ( outputs [ 0 ], skipspecialtokens = True ) print ( result ) 🏙️ Cyberpunk City SFW Nikon Z9 200mm f8 ISO 160, (giant rifle structure), flawless ornate architecture, cyberpunk, neon lights, busy street, realistic, ray tracing, hasselblad 🐉 Fantasy Dragon SFW masterpiece, best quality, cinematic lighting, 1girl, solo, 😈 Anime Succubus NSFW masterpiece, best quality, highly detailed background, intricate, 1girl, (full-face blush, aroused:1.3), long hair, medium breasts, nipples

This model is based on NousResearch's Llama 3.1 8B Instruct and is licensed under Apache 2.0. It utilizes the PEFT library.