Update README.md

README.md

@@ -16,8 +16,6 @@ license: other
 
 # FS-DFM (Few-Step Discrete Flow-Matching)
 
-This repository provides **FS-DFM checkpoints** from the paper:
-
 **FS-DFM: Fast and Accurate Long Text Generation with Few-Step Diffusion Language Model**  
 Amin Karimi Monsefi, Nikhil Bhendawade, Manuel R. Ciosici, Dominic Culver, Yizhe Zhang, Irina Belousova (Jan 9, 2026)  
 ArXiv: 2509.20624
@@ -31,7 +29,7 @@ FS-DFM is a **token-space diffusion / flow-matching language model** designed fo
 
 ### Checkpoint files
 - [`FS_DFM_checkpoint.pth`](FS_DFM_checkpoint.pth) — **FS-DFM 1.3B**, uniform source, **RK4 teacher distilled**
-- `DFM_checkpoint.pth` — **DFM 1.3B**, uniform source, DFM pretrained initialization
+- [`DFM_checkpoint.pth`](DFM_checkpoint.pth) — **DFM 1.3B**, uniform source, DFM pretrained initialization
 
 
 ---
@@ -78,18 +76,12 @@ Training/eval packing: documents packed into **1024-token** blocks (EOS appended
 
 ---
 
-## Reported behavior (paper)
-
-FS-DFM targets **long-horizon language modeling**. In the paper, **8-step sampling** is reported to reach **perplexity parity** with a **1024-step** discrete-flow baseline for **1024-token generation**, yielding up to **128× fewer model evaluations**.
-
-> For exact numbers/plots and ablations, refer to the paper.
-
----
-
-## How to use (recommended)
+## How to use
 
 FS-DFM uses custom discrete solvers and is not a drop-in `transformers` model. The intended usage is via the official training/evaluation scripts.
 
+> PLEASE SEE [OUR OFFICIAL GITHUB](https://github.com/apple/ml-fs-dfm/tree/main)
+
 ### 1) Install the official code
 ```bash
 git clone https://github.com/apple/ml-fs-dfm