| --- |
| task_categories: |
| - text-generation |
| language: |
| - en |
| size_categories: |
| - 1B<n<10B |
| --- |
| |
|  |
|
|
| **Dataset:** LLaDA-Sample-10BT |
| **Base:** `HuggingFaceFW/fineweb` (subset `sample-10BT`) |
| **Purpose:** Training LLaDA (Large Language Diffusion Models) |
|
|
| ## Preprocessing |
| - **Tokenizer:** `GSAI-ML/LLaDA-8B-Instruct` |
| - **Chunking:** Up to **4,096 tokens** per chunk (1% of chunks randomly sized between 1–4,096 tokens) |
| - **Noisy masking:** Applied with noise factor ε = 1×10⁻³ |
| - **Fields per chunk (PyTorch tensors):** |
| - `input_ids` |
| - `noisy_input_ids` |
| - `mask` |
| - `t` (time scalar) |
|
|
| ## Statistics |
| - **Total chunks:** ~2,520,000 |
| - **Shards:** 252 `.pt` files |
| - **Chunks per file:** 10,000 |
| - **Average file size:** ~702–708 MB |
| - **Total size:** ~166 GB |
|
|
| ## Usage |
| This dataset is used for training in the [LLaDA-from-scratch](https://github.com/FredyRivera-dev/LLaDA-from-scratch) GitHub repository, where you’ll find the full data pipeline and training scripts. |
|
|
