| --- |
| title: README |
| emoji: 🏆 |
| colorFrom: indigo |
| colorTo: green |
| sdk: static |
| pinned: true |
| --- |
| |
| # How to |
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| Please stick to the following guidelines when uploading resources. |
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| ### How to upload models |
| - Create a model repo using the following naming schema: `<use-case>-<pre-trained-model-name>-<training-type>-<version>` |
| - E.g., du-qwen3-4b-sft-v0 |
| - Keep the `<pre-trained-model-name>` as simple as possible (e.g., Apertus-8B-Instruct-2509 can become Apertus-8b) |
| - Mention the complete pre-trained-model-name in the model card |
| - **Important:** If this model will be deployed and used in production please append the "latest" keyword to the name and remove it from the repo that is currently marked as "latest" |
| - Upload the files to the created repo |
| - Write a model card with at least the following information |
| - Use Case (e.g., DU, NLG, ...) |
| - Pre-Trained Model Name |
| - Training Type (e.g., SFT, DPO, ...) |
| - Used Hyperparameters |
| - Version |
| - Used dataset(s) |
| - Where was it trained (e.g., Fireworks AI, Google Colab, ...) |
| - If trained on Colab please add the Link to the Notebook (both to Colab and GitLab) |
| - Add the repo to an existing collection, or create a new one if none applies |
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|
| ### How to upload datasets |
| - Create a dataset repo using the following naming schema: `<use-case>-<training-type>-<version>` |
| - Upload the files to the created repo |
| - Write a dataset card with at least the following information |
| - Summary |
| - Supported tasks |
| - Dataset structure |
| - Dataset creation |
| - Example for a dataset card: https://huggingface.co/datasets/novomind/nlg-sft-v1 |
