TencentARC / IBQ-Tokenizer-8192

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24-hour runs: -1
7-day runs: -3
30-day runs: -2
Model's Last Updated: December 30 2024

Introduction of IBQ-Tokenizer-8192

Model Details of IBQ-Tokenizer-8192

Taming Scalable Visual Tokenizer for Autoregressive Image Generation

Code: https://github.com/TencentARC/SEED-Voken

Paper: https://arxiv.org/abs/2412.02692

This repo is used for hosting IBQ’s checkpoints.

Introduction

We propose Index Backpropagation Quantization (IBQ), a new vector quantization method for the joint optimization of all codebook embeddings and the visual encoder, ensuring the consistent latent space.  IBQ enables scalable training of visual tokenizers and, for the first time, achieves a large-scale codebook (2^18) with high dimension (256) and high utilization.

Runs of TencentARC IBQ-Tokenizer-8192 on huggingface.co

5
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IBQ-Tokenizer-8192 huggingface.co

IBQ-Tokenizer-8192 huggingface.co is an AI model on huggingface.co that provides IBQ-Tokenizer-8192's model effect (), which can be used instantly with this TencentARC IBQ-Tokenizer-8192 model. huggingface.co supports a free trial of the IBQ-Tokenizer-8192 model, and also provides paid use of the IBQ-Tokenizer-8192. Support call IBQ-Tokenizer-8192 model through api, including Node.js, Python, http.

IBQ-Tokenizer-8192 huggingface.co Url

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https://huggingface.co/TencentARC/IBQ-Tokenizer-8192

IBQ-Tokenizer-8192 install

IBQ-Tokenizer-8192 is an open source model from GitHub that offers a free installation service, and any user can find IBQ-Tokenizer-8192 on GitHub to install. At the same time, huggingface.co provides the effect of IBQ-Tokenizer-8192 install, users can directly use IBQ-Tokenizer-8192 installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

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