| dataset_info: | |
| features: | |
| - name: text | |
| dtype: string | |
| - name: pos | |
| dtype: float64 | |
| splits: | |
| - name: train | |
| num_bytes: 5335090828.0 | |
| num_examples: 1002630 | |
| download_size: 3227201658 | |
| dataset_size: 5335090828.0 | |
| configs: | |
| - config_name: default | |
| data_files: | |
| - split: train | |
| path: data/train-* | |
| 1,378,234,368 tokens (using the Llama tokenizer, ~1.18b gpt4 tokens) from a deduped pile raw shard, filter len<896, ask-llm ([“How to Train Data-Efficient LLMs”](https://arxiv.org/abs/2402.09668)) w/ [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2), keep top 1/4 | |
| ``` | |
| { | |
| "text": "Once upon a time...", | |
| "pos": -5.654354325 | |
| } | |
| ``` |