Update README.md

README.md

@@ -24,7 +24,7 @@ The evaluation target is the vision encoder. Runs use different language backbon
 ## Model Zoo
 
 This Model Zoo covers the **70 visual tokenizers used in our paper**: **43 language-supervised**, **22 self-supervised**, and **5 discrete** tokenizers. 
-The current release provides both pretraining and finetuning checkpoints for all **65 continuous tokenizers** with each of the three main language backbones, plus **2** Qwen3-1.7B-Base runs. The **5 discrete tokenizers** are listed separately with their checkpoint availability. The repository-wide file totals above include all uploaded runs; the catalog below is restricted to the paper's 70 tokenizers.
+The current release provides both pretraining and finetuning checkpoints for all **65 continuous tokenizers** with each of the three main language backbones, plus **2** Qwen3-1.7B-Base runs. The **5 discrete tokenizers** are listed separately with their checkpoint availability. 
 
 ### Training data and checkpoint types
 
@@ -32,8 +32,6 @@ The current release provides both pretraining and finetuning checkpoints for all
 - **Finetuning Data — LLaVA-v1.5 mix665k (filtered):** the [LLaVA-v1.5 instruction mixture](https://huggingface.co/datasets/liuhaotian/LLaVA-Instruct-150K/blob/main/llava_v1_5_mix665k.json), using `llava_v1_5_mix665k_drop_ge8kchars.json`. The training configuration removes 395 examples with at least 8,000 characters of conversation text.
 - **Download:** `projector` downloads the pretraining `mm_projector.bin`; `finetuned` opens the finetuned checkpoint directory, including model weights, configuration, and language-tokenizer files. The frozen vision encoder must be supplied separately using the matching architecture and weights recorded in `config.json`. Pretraining projector weights alone are not instruction-tuned MLLMs.
 
-Tokenizer IDs below match the checkpoint directory names. Download links point to the main training-stage directories and exclude historical backup directories.
-
 ### Qwen2.5-1.5B-Instruct
 
 Base LLM: [Qwen/Qwen2.5-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct). **65 tokenizers**, each with pretraining and finetuning checkpoints.