vision language garment model

Providerackermannj
Categorymultimodal-representation
Licensemit
Downloads0
Stars0

Overview

The Vision Language Garment model is a specialized multimodal representation tool designed to bridge the gap between visual apparel data and textual descriptions. Unlike general-purpose vision models, this model is optimized for the nuances of fashion, focusing on garment attributes, materials, and stylistic features. For developers, this means more accurate tagging, improved semantic search for e-commerce catalogs, and a robust foundation for building virtual try-on or recommendation engines. It integrates easily into existing ML pipelines via the MIT license, providing a flexible, open-source alternative to proprietary fashion APIs. By mapping visual garment features into a shared latent space with language, it enables efficient cross-modal retrieval and precise attribute extraction without the noise typical of general image-to-text models.

Highlights

  • Specialized multimodal embeddings for precise fashion attribute mapping
  • Optimized for e-commerce search and garment tagging pipelines
  • Permissive MIT license for flexible commercial integration
  • High-fidelity alignment between apparel imagery and text descriptions

Usage

Install
# Install Hugging Face transformers
pip install transformers torch
SDK Usage
# Load model with transformers
from transformers import AutoModel, AutoTokenizer

model = AutoModel.from_pretrained("ackermannj/vision-language-garment-model")
tokenizer = AutoTokenizer.from_pretrained("ackermannj/vision-language-garment-model")

Hugging Face Download

We recommend downloading the model via the Hugging Face CLI or Hub SDK.

Guidance：Before downloading, install huggingface_hub with:

Guidance 
pip install -U huggingface_hub

CLI Download

Download the full repository

Download the full repository 
huggingface-cli download ackermannj/vision-language-garment-model

Download a single file to a local folder (e.g. config.json into ./dir)

Download a single file to a local folder (e.g. config.json into ./dir) 
huggingface-cli download ackermannj/vision-language-garment-model config.json --local-dir ./dir

See the official docs for more CLI options

SDK Download

SDK Download 
# 模型下载
from huggingface_hub import snapshot_download
model_dir = snapshot_download('ackermannj/vision-language-garment-model')

Git Download

Make sure git-lfs is installed first

Git Download 
git lfs install
git clone https://huggingface.co/ackermannj/vision-language-garment-model

To skip LFS large-file downloads, use:

Skip LFS 
GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/ackermannj/vision-language-garment-model

Model files are hosted on the Hugging Face Hub — download directly via HF CLI / SDK / Git, not through this site.

PyTorch / Transformers Usage

Install Transformers

Install Transformers 
pip install -U transformers torch

Load the model and run inference

Load the model and run inference 
from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained('ackermannj/vision-language-garment-model')
tokenizer = AutoTokenizer.from_pretrained('ackermannj/vision-language-garment-model')

Full Documentation

来源: HuggingFace

---
license: mit
datasets:

  • georgeNakayama/AIpparel

base_model:
  • meta-llama/Llama-3.1-8B-Instruct

---

View official source
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