Merge pull request #194 from helicalAI/update-ubuntu

Bump to ubuntu 24 & Fix typo in HyendaDNA notebook

.github/workflows/release.yml

@@ -10,7 +10,7 @@ permissions:
 
 jobs:
   fresh-install:
-    runs-on: ubuntu-20.04
+    runs-on: ubuntu-24.04
     steps:
       - name: Checkout repository
         uses: actions/checkout@v2

README.md

@@ -121,7 +121,6 @@ Within the `examples/notebooks` folder, open the notebook of your choice. We rec
 |[Cell-Type-Classification-Fine-Tuning.ipynb](./examples/notebooks/Cell-Type-Classification-Fine-Tuning.ipynb)|An example how to fine-tune different models on classification tasks.|[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/helicalAI/helical/blob/main/examples/notebooks/Cell-Type-Classification-Fine-Tuning.ipynb) |
 |[HyenaDNA-Fine-Tuning.ipynb](./examples/notebooks/HyenaDNA-Fine-Tuning.ipynb)|An example of how to fine-tune the HyenaDNA model on downstream benchmarks.|[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/helicalAI/helical/blob/main/examples/notebooks/HyenaDNA-Fine-Tuning.ipynb) |
 |[Cell-Gene-Cls-embedding-generation.ipynb](./examples/notebooks/Cell-Gene-Cls-embedding-generation.ipynb)|A notebook explaining the different embedding modes of single cell RNA models.|[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/helicalAI/helical/blob/main/examples/notebooks/Cell-Gene-Cls-embedding-generation.ipynb) |
-| Coming Soon | New models such as SCimilarity, scVI; benchmarking scripts; new use cases; others |
 
 ## Stuck somewhere ? Other ideas ?
 We are eager to help you and interact with you. Reach out via [email protected]. 

docs/index.md

@@ -99,7 +99,6 @@ Within the `example/notebooks` folder, open the notebook of your choice. We reco
 |[Cell-Type-Classification-Fine-Tuning.ipynb](./notebooks/Cell-Type-Classification-Fine-Tuning.ipynb)|An example how to fine-tune different models on classification tasks.|[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/helicalAI/helical/blob/main/examples/notebooks/Cell-Type-Classification-Fine-Tuning.ipynb) |
 |[HyenaDNA-Fine-Tuning.ipynb](./notebooks/HyenaDNA-Fine-Tuning.ipynb)|An example of how to fine-tune the HyenaDNA model on downstream benchmarks.|[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/helicalAI/helical/blob/main/examples/notebooks/HyenaDNA-Fine-Tuning.ipynb) |
 |[Cell-Gene-Cls-embedding-generation.ipynb](./examples/notebooks/Cell-Gene-Cls-embedding-generation.ipynb)|A notebook explaining the different embedding modes of single cell RNA models.|[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/helicalAI/helical/blob/main/examples/notebooks/Cell-Gene-Cls-embedding-generation.ipynb) |
-| Coming Soon | New models such as SCimilarity, scVI; benchmarking scripts; new use cases; others |
 
 ## Stuck somewhere ? Other ideas ?
 We are eager to help you and interact with you. Reach out via [email protected]. 

examples/notebooks/Hyena-DNA-Inference.ipynb

@@ -501,8 +501,8 @@
    ],
    "source": [
     "X_unseen, y_unseen = get_model_inputs(dataset[\"test\"])\n",
-    "#np.save(f\"data/test/x_{label}_norm_256.npy\")\n",
-    "#np.save(f\"data/test/y_{label}_norm_256.npy\")"
+    "#np.save(f\"data/test/x_{label}_norm_256.npy\", X_unseen)\n",
+    "#np.save(f\"data/test/y_{label}_norm_256.npy\", y_unseen)"
    ]
   },
   {

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "helical"
-version = "0.0.1a22"
+version = "0.0.1a23"
 authors = [
   { name="Helical Team", email="[email protected]" },
 ]