| license: apache-2.0 | |
| task_categories: | |
| - feature-extraction | |
| - sentence-similarity | |
| language: | |
| - fr | |
| - en | |
| tags: | |
| - sentence-transformers | |
| - feature-extraction | |
| - sentence-similarity | |
| - mteb | |
| - Query | |
| - Document | |
| - Argument | |
| - Counter | |
| - Boost | |
| pretty_name: information retrieval system | |
| size_categories: | |
| - n<1K | |
| # deepspeed-from-new-new-docker Dataset | |
| ## Dataset Description | |
| The dataset "information retrieval system" is a generated dataset designed to support the development of domain specific embedding models for retrieval tasks. | |
| ## Associated Model | |
| This dataset was used to train the [**deepspeed-from-new-new-docker**](https://huggingface.co/fine-tuned/deepspeed-from-new-new-docker) model. | |
| ## How to Use | |
| To use this dataset for model training or evaluation, you can load it using the Hugging Face `datasets` library as follows: | |
| ```python | |
| from datasets import load_dataset | |
| dataset = load_dataset("fine-tuned/deepspeed-from-new-new-docker") | |
| print(dataset['test'][0]) | |
| ``` | |