Updates for the release.

Author: botev

CONTRIBUTING.md

@@ -1,6 +1,6 @@
 # How to Contribute
 
-We are currently evaluating whether to accept external PRs.
+We are currently not accepting external PRs.
 
 ## Before you begin
 
@@ -22,11 +22,3 @@ sign a new one.
 
 This project follows [Google's Open Source Community
 Guidelines](https://opensource.google/conduct/).
-
-## Contribution process
-
-### Code Reviews
-
-All submissions, including submissions by project members, require review. We
-use [GitHub pull requests](https://docs.github.com/articles/about-pull-requests)
-for this purpose.

colabs/fine_tuning_tutorial_jax.ipynb

@@ -91,6 +91,7 @@
         "1. Visit https://www.kaggle.com/ and create an account.\n",
         "2. Go to your account settings, then the 'API' section.\n",
         "3. Click 'Create new token' to download your key.\n",
+        "4. You can either login using the UI interface or by setting your Kaggle username and key via the Colab secrets.\n",
         "\n",
         "You will also need to acknowledge the Terms and Conditions of the RecrurrentGemma models on https://www.kaggle.com/models/google/recurrentgemma/ in order to be able to download the model weights and the tokenizer.\n",
         "\n",
@@ -105,8 +106,15 @@
       },
       "outputs": [],
       "source": [
+        "import os\n",
+        "from google.colab import userdata\n",
         "import kagglehub\n",
-        "kagglehub.login()"
+        "\n",
+        "try:\n",
+        "  os.environ[\"KAGGLE_KEY\"] = userdata.get(\"KAGGLE_KEY\")\n",
+        "  os.environ[\"KAGGLE_USERNAME\"] = userdata.get(\"KAGGLE_USERNAME\")\n",
+        "except userdata.SecretNotFoundError:\n",
+        "  kagglehub.login()"
       ]
     },
     {
@@ -535,7 +543,10 @@
       "source": [
         "# Load parameters\n",
         "params =  recurrentgemma.load_parameters(ckpt_path, \"single_device\")\n",
-        "config = recurrentgemma.GriffinConfig.from_flax_params_or_variables(params)\n",
+        "config = recurrentgemma.GriffinConfig.from_flax_params_or_variables(\n",
+        "    params,\n",
+        "    preset=recurrentgemma.Preset.RECURRENT_GEMMA_2B_V1,\n",
+        ")\n",
         "model = recurrentgemma.Griffin(config)"
       ]
     },