feat: improve notebook reade

notebooks/00_quickstart_inference.ipynb

@@ -16,7 +16,9 @@
         "\n",
         "1. Load tokenizers + models\n",
         "2. Run a forward pass on a DNA sequence window\n",
-        "3. Inspect key outputs"
+        "3. Inspect key outputs\n",
+        "\n",
+        "> **Note for Google Colab users:** This notebook is compatible with Colab! For faster inference, make sure to enable GPU: Runtime → Change runtime type → GPU (T4 or better recommended)."
       ]
     },
     {
@@ -24,9 +26,9 @@
       "id": "5d58bf1d",
       "metadata": {},
       "source": [
-        "## 0) Install dependencies\n",
+        "## 0) Colab Setup (if running on Google Colab)\n",
         "\n",
-        "Skip if already installed."
+        "This cell detects if you're running on Google Colab and sets up the environment accordingly."
       ]
     },
     {

notebooks/01_tracks_prediction.ipynb

@@ -9,6 +9,8 @@
         "\n",
         "This notebook demonstrates how to use the **NTv3 post-trained model** to predict functional genomics tracks and genomic element annotations from DNA sequences.\n",
         "\n",
+        "> **Note for Google Colab users:** This notebook is compatible with Colab! For faster inference, make sure to enable GPU: Runtime → Change runtime type → GPU (T4 or better recommended).\n",
+        "\n",
         "## Overview\n",
         "\n",
         "Given a genomic window from the **human genome (hg38)**, the model performs inference and generates:\n",
@@ -36,12 +38,14 @@
       "id": "4997c547",
       "metadata": {},
       "source": [
-        "## 0) Install dependencies"
+        "## 0) Colab Setup (if running on Google Colab)\n",
+        "\n",
+        "This cell detects if you're running on Google Colab and sets up the environment accordingly."
       ]
     },
     {
       "cell_type": "code",
-      "execution_count": 23,
+      "execution_count": null,
       "id": "0ff509fd",
       "metadata": {},
       "outputs": [
@@ -55,7 +59,8 @@
         }
       ],
       "source": [
-        "!pip -q install \"transformers>=4.55\" \"huggingface_hub>=0.23\" safetensors torch pyfaidx requests seaborn"
+        "# Install dependencies\n",
+        "!pip -q install \"transformers>=4.55\" \"huggingface_hub>=0.23\" safetensors torch pyfaidx requests seaborn matplotlib"
       ]
     },
     {
@@ -162,7 +167,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 4,
+      "execution_count": null,
       "id": "8c20066a",
       "metadata": {},
       "outputs": [
@@ -177,7 +182,7 @@
         }
       ],
       "source": [
-        "def download_ucsc_chrom_fasta(chrom: str, assembly: str, out_dir: str = f\"./genomes/{assembly}\") -> str:\n",
+        "def download_ucsc_chrom_fasta(chrom: str, assembly: str, out_dir: str = f\"./{assembly}\") -> str:\n",
         "    \"\"\"Download a single chromosome FASTA from UCSC and return local path.\"\"\"\n",
         "    os.makedirs(out_dir, exist_ok=True)\n",
         "    gz_path = os.path.join(out_dir, f\"{chrom}.fa.gz\")\n",