Bring release into main

README.md

@@ -121,16 +121,18 @@ Within the `examples/notebooks` folder, open the notebook of your choice. We rec
 | ----------- | ----------- |----------- |                                                        
 |[Quick-Start-Tutorial.ipynb](./examples/notebooks/Quick-Start-Tutorial.ipynb)| A tutorial to quickly get used to the helical package and environment. | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/helicalAI/helical/blob/main/examples/notebooks/Quick-Start-Tutorial.ipynb)|
 |[Helix-mRNA.ipynb](./examples/notebooks/Helix-mRNA.ipynb)|An example of how to use the Helix-mRNA model.|[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/helicalAI/helical/blob/main/examples/notebooks/Helix-mRNA.ipynb) |
-|[Geneformer-vs-TranscriptFormer.ipynb](./examples/notebooks/Geneformer-vs-TranscriptFormer.ipynb) | Zero-Shot Reference Mapping with Geneformer & UCE and compare the outcomes. | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/helicalAI/helical/blob/main/examples/notebooks/Geneformer-vs-TranscriptFormer.ipynb) |
+|[Geneformer-vs-TranscriptFormer.ipynb](./examples/notebooks/Geneformer-vs-TranscriptFormer.ipynb) | Zero-Shot Reference Mapping with Geneformer & TranscriptFormer and compare the outcomes. | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/helicalAI/helical/blob/main/examples/notebooks/Geneformer-vs-TranscriptFormer.ipynb) |
 |[Hyena-DNA-Inference.ipynb](./examples/notebooks/Hyena-DNA-Inference.ipynb)|An example how to do probing with HyenaDNA by training a neural network on 18 downstream 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/Hyena-Dna-Inference.ipynb) |
 |[Cell-Type-Annotation.ipynb](./examples/notebooks/Cell-Type-Annotation.ipynb)|An example how to do probing with scGPT by training a neural network to predict cell type annotations.|[![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-Annotation.ipynb) |
 |[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) |
 
 ## Stuck somewhere ? Other ideas ?
-We are eager to help you and interact with you. Reach out via support@helical-ai.com. 
-You can also open github issues here.
+We are eager to help you and interact with you:
+- Join our [Slack channel](https://dk1sxv04.eu1.hubspotlinksfree.com/Ctc/L2+113/dk1sxv04/VWtlqj8M7nFNVf1vhw52bPfMW8wLjj95ptQw7N1k24YY3m2ndW8wLKSR6lZ3ldW7fZmPx5PxJ2lW8mYJtq5xWH5BVsxw821cWpdKW8CYXdj753XHSW8b5vG-7PTQ2LW1zs6x622rZxDW6930hX7RPKh3N5-trBXyRHkwVfJ3Zs3wRQV_N5NbYL3-lm47W1HvYX63pJp9cW6QXY-x6QsWMTW8G5jZh7T4vphN4Qtr7dMCxlJW8rM1-Y42pS-PW5sfJbh4FyRMhW5mHPkD4yCl56W36YW1_4GpPrGW7-sRYG1gXy8hMXqK6Sp5p69W8YTpvd3tC80SW2PTYtr6hP0dxW863B5F4KNCYkVFSWl390bSlQW78rxWn7JbS3LW14ZJ735n7SpFVSVlQr7lm7vwVlWslf6g9JRQf8mBL3b04) where you can discuss applications of bio foundation models.
+- Reach out via support@helical-ai.com. 
+- You can also open Github issues [here](https://github.com/helicalAI/helical/issues).
 
 ## Why should I use Helical & what to expect in the future?
 If you are (or plan to) working with bio foundation models s.a. Geneformer or UCE on RNA and DNA data, Helical will be your best buddy! We provide and improve on:
@@ -169,7 +171,7 @@ You can find the Licenses for each model implementation in the model repositorie
 - [scGPT](https://github.com/helicalAI/helical/blob/release/helical/models/scgpt/LICENSE)
 - [Geneformer](https://github.com/helicalAI/helical/blob/release/helical/models/geneformer/LICENSE)
 - [UCE](https://github.com/helicalAI/helical/blob/release/helical/models/uce/LICENSE)
-- [TranscriptFormer](https://github.com/helicalAI/helical/blob/release/helical/models/transcriptformer/LICENSE)
+- [TranscriptFormer](https://github.com/helicalAI/helical/blob/release/helical/models/transcriptformer/LICENSE.md)
 - [HyenaDNA](https://github.com/helicalAI/helical/blob/release/helical/models/hyena_dna/LICENSE)
 - [Evo2](https://github.com/helicalAI/helical/blob/release/helical/models/evo_2/LICENSE)
 
@@ -180,7 +182,7 @@ Please use this BibTeX to cite this repository in your publications:
 ```bibtex
 @software{allard_2024_13135902,
   author       = {Helical Team},
-  title        = {helicalAI/helical: v0.0.1a27},
+  title        = {helicalAI/helical: v1.0.0},
   month        = nov,
   year         = 2024,
   publisher    = {Zenodo},

docs/index.md

@@ -101,19 +101,25 @@ Within the `example/notebooks` folder, open the notebook of your choice. We reco
 | ----------- | ----------- |----------- |                                                        
 |[Quick-Start-Tutorial.ipynb](./notebooks/Quick-Start-Tutorial.ipynb)| A tutorial to quickly get used to the helical package and environment. | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/helicalAI/helical/blob/main/examples/notebooks/Quick-Start-Tutorial.ipynb)|
 |[Helix-mRNA.ipynb](./notebooks/Helix-mRNA.ipynb)|An example of how to use the Helix-mRNA model.|[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/helicalAI/helical/blob/main/examples/notebooks/Helix-mRNA.ipynb) |
-|[Geneformer-vs-TranscriptFormer.ipynb](./notebooks/Geneformer-vs-TranscriptFormer.ipynb) | Zero-Shot Reference Mapping with Geneformer & UCE and compare the outcomes. | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/helicalAI/helical/blob/main/examples/notebooks/Geneformer-vs-TranscriptFormer.ipynb) |
+|[Geneformer-vs-TranscriptFormer.ipynb](./notebooks/Geneformer-vs-TranscriptFormer.ipynb) | Zero-Shot Reference Mapping with Geneformer & TranscriptFormer and compare the outcomes. | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/helicalAI/helical/blob/main/examples/notebooks/Geneformer-vs-TranscriptFormer.ipynb) |
 |[Hyena-DNA-Inference.ipynb](./notebooks/Hyena-DNA-Inference.ipynb)|An example how to do probing with HyenaDNA by training a neural network on 18 downstream 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/Hyena-DNA-Inference.ipynb)|
 |[Cell-Type-Annotation.ipynb](./notebooks/Cell-Type-Annotation.ipynb)|An example how to do probing with scGPT by training a neural network to predict cell type annotations.|[![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-Annotation.ipynb) |
 |[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) |
 
-## Stuck somewhere? Other ideas?
-We are eager to help you and interact with you. Reach out via support@helical-ai.com. 
-You can also open github issues here.
+## Stuck somewhere ? Other ideas ?
+We are eager to help you and interact with you:
+
+
+- Join our [Slack channel](https://dk1sxv04.eu1.hubspotlinksfree.com/Ctc/L2+113/dk1sxv04/VWtlqj8M7nFNVf1vhw52bPfMW8wLjj95ptQw7N1k24YY3m2ndW8wLKSR6lZ3ldW7fZmPx5PxJ2lW8mYJtq5xWH5BVsxw821cWpdKW8CYXdj753XHSW8b5vG-7PTQ2LW1zs6x622rZxDW6930hX7RPKh3N5-trBXyRHkwVfJ3Zs3wRQV_N5NbYL3-lm47W1HvYX63pJp9cW6QXY-x6QsWMTW8G5jZh7T4vphN4Qtr7dMCxlJW8rM1-Y42pS-PW5sfJbh4FyRMhW5mHPkD4yCl56W36YW1_4GpPrGW7-sRYG1gXy8hMXqK6Sp5p69W8YTpvd3tC80SW2PTYtr6hP0dxW863B5F4KNCYkVFSWl390bSlQW78rxWn7JbS3LW14ZJ735n7SpFVSVlQr7lm7vwVlWslf6g9JRQf8mBL3b04) where you can discuss applications of bio foundation models.
+- Reach out via support@helical-ai.com. 
+- You can also open Github issues [here](https://github.com/helicalAI/helical/issues).
 
 ## Why should I use Helical & what to expect in the future?
 If you are (or plan to) working with bio foundation models s.a. Geneformer or UCE on RNA and DNA data, Helical will be your best buddy! We provide and improve on:
+
+
 - Up-to-date model library
 - A unified API for all models
 - User-facing abstractions tailored to computational biologists, researchers & AI developers
@@ -160,11 +166,11 @@ Please use this BibTeX to cite this repository in your publications:
 ```bibtex
 @software{allard_2024_13135902,
   author       = {Helical Team},
-  title        = {helicalAI/helical: v0.0.1a27},
+  title        = {helicalAI/helical: v1.0.0},
   month        = nov,
   year         = 2024,
   publisher    = {Zenodo},
-  version      = {0.0.1a27},
+  version      = {1.0.0},
   doi          = {10.5281/zenodo.13135902},
   url          = {https://doi.org/10.5281/zenodo.13135902}
 }

examples/notebooks/Geneformer-vs-TranscriptFormer.ipynb

@@ -26,10 +26,10 @@
     "\n",
     "\n",
     "### 🧬 About Helical:\n",
-    "Helical provides an open-source framework for and gathers state-of-the-art pre-trained genomics and transciptomics bio foundation models. Still work in progress, but we look forward to interacting with the community to build meaningful things. You can directly reach us:\n",
-    "- support@helical-ai.com (slack-channel incoming). We answer within hours! Reach out if you have questions, ideas, improvement suggestions, colab, ...\n",
-    "- [Github](https://github.com/helicalAI/helical-package/issues). On our github in the issue section \n",
-    "\n",
+    "Helical provides an open-source framework for and gathers state-of-the-art pre-trained genomics and transciptomics bio foundation models. We look forward to interacting with the community to build meaningful things. You can directly reach us:\n",
+    "- Join our [Slack channel](https://dk1sxv04.eu1.hubspotlinksfree.com/Ctc/L2+113/dk1sxv04/VWtlqj8M7nFNVf1vhw52bPfMW8wLjj95ptQw7N1k24YY3m2ndW8wLKSR6lZ3ldW7fZmPx5PxJ2lW8mYJtq5xWH5BVsxw821cWpdKW8CYXdj753XHSW8b5vG-7PTQ2LW1zs6x622rZxDW6930hX7RPKh3N5-trBXyRHkwVfJ3Zs3wRQV_N5NbYL3-lm47W1HvYX63pJp9cW6QXY-x6QsWMTW8G5jZh7T4vphN4Qtr7dMCxlJW8rM1-Y42pS-PW5sfJbh4FyRMhW5mHPkD4yCl56W36YW1_4GpPrGW7-sRYG1gXy8hMXqK6Sp5p69W8YTpvd3tC80SW2PTYtr6hP0dxW863B5F4KNCYkVFSWl390bSlQW78rxWn7JbS3LW14ZJ735n7SpFVSVlQr7lm7vwVlWslf6g9JRQf8mBL3b04) where you can discuss applications of bio foundation models.\n",
+    "- Reach out via support@helical-ai.com. \n",
+    "- You can also open Github issues [here](https://github.com/helicalAI/helical/issues).\n",
     "\n",
     "### Before you start\n",
     "Be sure to install the Helical python package as descibed in [Installation](https://github.com/helicalAI/helical-package)."

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "helical"
-version = "0.0.1a29"
+version = "1.0.0"
 authors = [
   { name="Helical Team", email="support@helical-ai.com" },
 ]