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---
language:
- en
base_model: louisbrulenaudet/Pearl-3x7B
library_name: mlx
tags:
- moe
- frankenmoe
- merge
- mergekit
- lazymergekit
- dvilasuero/DistilabelBeagle14-7B
- beowolx/CodeNinja-1.0-OpenChat-7B
- WizardLM/WizardMath-7B-V1.1
- Maths
- Code
- Python
pipeline_tag: text-generation
license: apache-2.0
---
<center><img src='https://i.imgur.com/0xFTuAX.png' width='450px'></center>
# mlx-community/Pearl-3x7B
This model was converted to MLX format from [`louisbrulenaudet/Pearl-3x7B`]() using mlx-vlm version **0.16.1**.
Refer to the [original model card](louisbrulenaudet/Pearl-3x7B) for more details on the model.
## Use with mlx
```bash
pip install -U mlx-vlm
python -m mlx_vlm.generate --model mlx-community/Pearl-3x7B --max-tokens 100 --temp 0.0
```
```python
from mlx_lm import load, generate
model, tokenizer = load("mlx-community/Pearl-3x7B")
response = generate(model, tokenizer, prompt="hello", verbose=True)
```
## Citing & Authors
If you use this code in your research, please use the following BibTeX entry.
```BibTeX
@misc{louisbrulenaudet2024,
author = {Louis Brulé Naudet},
title = {Pearl-3x7B, an xtraordinary Mixture of Experts (MoE) for data science},
year = {2024}
howpublished = {\url{https://huggingface.co/mlx-community/Pearl-3x7B}},
}
```
## Feedback
If you have any feedback, please reach out at [[email protected]](mailto:[email protected]). |