docs: Open-in-Colab badge + point to notebook.ipynb

README.md

@@ -29,7 +29,11 @@ metrics:
 <div align="center">
   <a href="https://huggingface.co/RadeAI/Rade-ASR-CTC-3B-fa">🤗 Model</a> |
   <a href="https://github.com/facebookresearch/omnilingual-asr">🐙 Base (Omnilingual ASR)</a> |
-  <a href="https://huggingface.co/RadeAI/Rade-ASR-CTC-3B-fa/blob/main/inference_colab.ipynb">📓 Colab notebook</a>
+  <a href="https://huggingface.co/RadeAI/Rade-ASR-CTC-3B-fa/blob/main/notebook.ipynb">📓 Notebook</a>
+</div>
+
+<div align="center">
+  <a href="https://huggingface.co/RadeAI/Rade-ASR-CTC-3B-fa/colab"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in Colab"></a>
 </div>
 
 > **TL;DR** — A fast, non-autoregressive (CTC) speech-to-text model specialized for **Persian**, built on top of Meta's 3-billion-parameter Omnilingual ASR encoder. It transcribes Persian audio clips (≤ 40 s) and runs **~199× faster than real time** in fp16 on a single RTX 4090. On FLEURS Persian it reaches **WER ≈ 11% / CER ≈ 3.4%** (normalized).
@@ -79,7 +83,7 @@ FP16 and FP32 produce **identical transcripts**, so FP16 is the recommended defa
 | **`model_fp16.pt`** | Consolidated **fp16** weights, single file | **~6.2 GB** | **Recommended.** Smaller, faster download; fp16 inference. |
 | `pp_00/tp_00/sdp_00.pt`, `sdp_01.pt` | Original **fp32** FSDP checkpoint shards | ~12 GB | If you want full fp32 precision weights. |
 | `config.json` | Model metadata (arch, tokenizer, vocab) | — | Read by tooling; you don't load it directly. |
-| `inference_colab.ipynb` | Ready-to-run Colab notebook | — | One-click demo. |
+| `notebook.ipynb` | Ready-to-run Colab/Kaggle notebook | — | One-click demo (powers the "Open in Colab" button). |
 
 > Both weight files produce **identical transcripts** at fp16. The single `model_fp16.pt` is just half the download — prefer it unless you specifically need the fp32 master weights.
 
@@ -136,7 +140,7 @@ text = pipe.transcribe(["sample_fa.wav"], lang=["pes_Arab"], batch_size=1)
 print(text[0])
 ```
 
-A ready-to-run notebook is provided: **[`inference_colab.ipynb`](https://huggingface.co/RadeAI/Rade-ASR-CTC-3B-fa/blob/main/inference_colab.ipynb)**.
+A ready-to-run notebook is provided: **[`notebook.ipynb`](https://huggingface.co/RadeAI/Rade-ASR-CTC-3B-fa/blob/main/notebook.ipynb)** — or just click **[Open in Colab](https://huggingface.co/RadeAI/Rade-ASR-CTC-3B-fa/colab)** (also in the **"Use this model"** menu at the top of this page).
 
 ## Limitations
 
@@ -178,7 +182,7 @@ Built and maintained by **Rade AI**. For questions, collaboration, or custom Per
 - در fp16 فقط **۶.۴ گیگابایت VRAM** می‌خواهد (یک GPU ۱۶ گیگ کافی است).
 - روی دیتاستِ FLEURS فارسی (با نرمال‌سازیِ hazm): **WER ۱۰.۸٪** و **CER ۳.۴٪**.
 
-نحوه‌ی استفاده در بخش انگلیسیِ بالا و در نوت‌بوک `inference_colab.ipynb` آمده است.
+نحوه‌ی استفاده در بخش انگلیسیِ بالا آمده. برای تستِ سریع، دکمه‌ی **Open in Colab** (بالای همین صفحه، منوی «Use this model») یا نوت‌بوکِ `notebook.ipynb` رو باز کن.
 
 **ارتباط با راده:** تلگرام [@Rade_admin](https://t.me/Rade_admin) — تلفن: ۰۹۳۶۸۶۴۷۴۹۹