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task_categories:
- feature-extraction
language:
- en
size_categories:
- 100K<n<1M
---
# ALLNLI for Mimicking Vector Space
## Description
This dataset contains sentences from the [ALLNLI](https://huggingface.co/datasets/sentence-transformers/all-nli) dataset, which is a combination of the [SNLI](https://huggingface.co/datasets/stanfordnlp/snli) and [MultiNLI](https://huggingface.co/datasets/nyu-mll/multi_nli) datasets. It is designed for training a student model to mimic the vector space of a teacher model. This dataset is particularly useful for tasks involving embedding loss computation, where the student model learns to replicate the teacher model's embeddings. All the "anchor" and "positive" sentences from the ALLNLI dataset are included, with redundant sentences removed.
## Usage
You can load the dataset using the Hugging Face `datasets` library:
```python
from datasets import load_dataset
dataset = load_dataset('langformers/allnli-mimic-embedding') |