Upload inference_example.ipynb

inference_example.ipynb

@@ -25,7 +25,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "model = AutoModel.from_pretrained(\"InstaDeepAI/segment_enformer\", trust_remote_code=True)"
+    "model = AutoModel.from_pretrained(\"InstaDeepAI/segment_borzoi\", trust_remote_code=True)"
    ]
   },
   {
@@ -50,8 +50,8 @@
     "\n",
     "    Returns:\n",
     "        torch.Tensor: One-hot encoded\n",
-    "            - If `sequences` is just one sequence (str), output shape is (196608, 4)\n",
-    "            - If `sequences` is a list of sequences, output shape is (num_sequences, 196608, 4)\n",
+    "            - If `sequences` is just one sequence (str), output shape is (seq_len, 4), seq_len being the length of a sequence\n",
+    "            - If `sequences` is a list of sequences, output shape is (num_sequences, seq_len, 4)\n",
     "            \n",
     "    \"\"\"\n",
     "    one_hot_map = {\n",
@@ -93,7 +93,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "sequences = [\"A\"*196608, \"G\"*196608]\n",
+    "sequences = [\"A\"*524_288, \"G\"*524_288]\n",
     "one_hot_encoding = encode_sequences(sequences)"
    ]
   },