Link paper and GitHub repository, add task category
Browse filesHi! I'm Niels from the community science team at Hugging Face. I'm opening this PR to improve the dataset card:
- Added `task_categories: [text-generation]` to the metadata.
- Linked the dataset to its corresponding paper: [Rethinking Language Model Scaling under Transferable Hypersphere Optimization](https://huggingface.co/papers/2603.28743).
- Added a link to the official GitHub repository: [microsoft/ArchScale](https://github.com/microsoft/ArchScale).
README.md
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license: apache-2.0
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# Prolong_64K_v2_Llama2_Tokenizer
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This is the Prolong_64K dataset, tokenized using the [Llama-2-7b-hf tokenizer](https://github.com/microsoft/Samba/blob/main/scripts/prepare_slimpajama.py#L22) for use in Samba-style training.
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👉 You can download and unzip the dataset from: [prolong_64K_v2.zip](https://huggingface.co/datasets/jsun/Prolong_64K_v2_Llama2_Tokenizer/blob/main/prolong_64K_v2.zip)
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```bash
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sudo apt install zip # Ubuntu
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unzip prolong_64K_v2.zip -d prolong_64K_v2
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```
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license: apache-2.0
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task_categories:
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- text-generation
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# Prolong_64K_v2_Llama2_Tokenizer
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This is the Prolong_64K dataset, tokenized using the [Llama-2-7b-hf tokenizer](https://github.com/microsoft/Samba/blob/main/scripts/prepare_slimpajama.py#L22) for use in Samba-style training.
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This dataset was used in the research paper: [Rethinking Language Model Scaling under Transferable Hypersphere Optimization](https://huggingface.co/papers/2603.28743).
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The official training codebase can be found at [GitHub - microsoft/ArchScale](https://github.com/microsoft/ArchScale).
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## Download
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👉 You can download and unzip the dataset from: [prolong_64K_v2.zip](https://huggingface.co/datasets/jsun/Prolong_64K_v2_Llama2_Tokenizer/blob/main/prolong_64K_v2.zip)
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```bash
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sudo apt install zip # Ubuntu
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unzip prolong_64K_v2.zip -d prolong_64K_v2
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```
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## Usage
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Once extracted, the dataset can be loaded using the [PackedDataset](https://github.com/microsoft/Samba/blob/383c016f2fb20ce75eed777761e1a4456c87b2b0/lit_gpt/packed_dataset.py#L33) class from the Samba/ArchScale codebase.
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Example training scripts utilizing this data format are provided in the [ArchScale repository](https://github.com/microsoft/ArchScale).
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