🧠

Model

Sktwatch Dreambooth Lora

Name: Sktwatch Dreambooth Lora
Author: jesslee0855

by jesslee0855 hf-model--jesslee0855--sktwatch-dreambooth-lora

Free2AITools Nexus Index

37.3 Top 100%

S: Semantic 50

A: Authority 0

P: Popularity 1

R: Recency 97

Q: Quality 50

Tech Context

Vital Performance

6 DL / 30D

0.0%

Source →

Audited 37.3 FNI Score

Tiny - Params

- Context

6 Downloads

Restricted CREATIVEML License

Model Information Summary
Entity Passport
Registry ID	hf-model--jesslee0855--sktwatch-dreambooth-lora
License	creativeml-openrail-m
Provider	huggingface

📜

Cite this model

Academic & Research Attribution

BibTeX

@misc{hf_model__jesslee0855__sktwatch_dreambooth_lora,
  author = {jesslee0855},
  title = {Sktwatch Dreambooth Lora Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/jesslee0855/sktwatch-dreambooth-lora}},
  note = {Accessed via Free2AITools Knowledge Fortress}
}

APA Style

jesslee0855. (2026). Sktwatch Dreambooth Lora [Model]. Free2AITools. https://huggingface.co/jesslee0855/sktwatch-dreambooth-lora

🔬Technical Deep Dive

Full Specifications [+]

Quick Commands

🤗 HF Download

huggingface-cli download jesslee0855/sktwatch-dreambooth-lora

⚖️ Free2AITools Nexus Index V2.0

Methodology Index Protocol

Semantic (S) 50

Authority (A) 0

Popularity (P) 1

Recency (R) 97

Quality (Q) 50

💬 Index Insight

FNI V2.0 for Sktwatch Dreambooth Lora: Semantic (S:50), Authority (A:0), Popularity (P:1), Recency (R:97), Quality (Q:50).

Free2AITools Nexus Index

Verification Authority

HuggingFace API GitHub Metadata Arxiv Citation DB System Audit

Unbiased Data Node Refresh: VFS Live

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🚀 What's Next?

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Compare Benchmarks

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⚡

Technical Deep Dive

LoRA DreamBooth - jesslee0855/sktwatch-dreambooth-lora

These are LoRA adaption weights for stable-diffusion-v1-5/stable-diffusion-v1-5. The weights were trained on a photo of sktwatch watch using DreamBooth. You can find some example images in the following.

LoRA for the text encoder was enabled: False.

Intended uses & limitations

How to use

python

# TODO: add an example code snippet for running this diffusion pipeline

Limitations and bias

[TODO: provide examples of latent issues and potential remediations]

Training details

[TODO: describe the data used to train the model]

⚠️ Incomplete Data

Some information about this model is not available. Use with Caution - Verify details from the original source before relying on this data.

View Original Source →

📝 Limitations & Considerations

• Benchmark scores may vary based on evaluation methodology and hardware configuration.
• VRAM requirements are estimates; actual usage depends on quantization and batch size.
• FNI scores are relative rankings and may change as new models are added.
⚠ License Unknown: Verify licensing terms before commercial use.

Social Proof

HuggingFace Hub

6Downloads

Hub Discussions

🤗 Data Source: Hugging Face ↗

🔄 Daily sync (03:00 UTC)

AI Summary: Based on Hugging Face metadata. Not a recommendation.

📊 FNI Methodology 📚 Knowledge Baseℹ️ Verify with original source

🛡️ Model Transparency Report

Technical metadata sourced from upstream repositories.

Open Metadata

🆔 Identity & Source

id: hf-model--jesslee0855--sktwatch-dreambooth-lora
slug: jesslee0855--sktwatch-dreambooth-lora
source: huggingface
author: jesslee0855
license: creativeml-openrail-m
tags: diffusers, tensorboard, text-to-image, lora, diffusers-training, stable-diffusion, stable-diffusion-diffusers, license:creativeml-openrail-m, region:us

⚙️ Technical Specs

architecture: null
params billions: null
context length: null
pipeline tag: text-to-image

📊 Engagement & Metrics

downloads: 6
stars: 0
forks: 0

Data indexed from public sources. Updated daily.