mergekit-configs
收藏魔搭社区2025-11-27 更新2025-11-03 收录
下载链接:
https://modelscope.cn/datasets/louisbrulenaudet/mergekit-configs
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资源简介:
## Dataset Description
- **Repository:** https://huggingface.co/datasets/louisbrulenaudet/mergekit-configs
- **Leaderboard:** N/A
- **Point of Contact:** [Louis Brulé Naudet](mailto:louisbrulenaudet@icloud.com)
<img src="assets/thumbnail.webp">
# MergeKit-configs: access all Hub architectures and automate your model merging process
This dataset facilitates the search for compatible architectures for model merging with MergeKit, streamlining the automation of high-performance merge searches. It provides a snapshot of the Hub’s configuration state, eliminating the need to manually open configuration files.
```python
import polars as pl
# Login using e.g. `huggingface-cli login` to access this dataset
df = pl.read_parquet('hf://datasets/louisbrulenaudet/mergekit-configs/data/raw-00000-of-00001.parquet')
result = (
df.groupby(
[
"architectures",
"hidden_size",
"model_type",
"intermediate_size"
]
).agg(
pl.struct([pl.col("id")]).alias("models")
)
)
```
## Citing & Authors
If you use this dataset in your research, please use the following BibTeX entry.
```BibTeX
@misc{HFforLegal2024,
author = {Louis Brulé Naudet},
title = {MergeKit-configs: access all Hub architectures and automate your model merging process},
year = {2024}
howpublished = {\url{https://huggingface.co/datasets/louisbrulenaudet/mergekit-configs}},
}
```
## Feedback
If you have any feedback, please reach out at [louisbrulenaudet@icloud.com](mailto:louisbrulenaudet@icloud.com).
## 数据集说明
- **仓库地址:** https://huggingface.co/datasets/louisbrulenaudet/mergekit-configs
- **排行榜:** 无
- **联系人:** [Louis Brulé Naudet](mailto:louisbrulenaudet@icloud.com)

# MergeKit-configs:接入所有Hugging Face Hub架构,自动化模型合并流程
本数据集可辅助查找适配MergeKit(模型合并工具)的模型合并兼容架构,简化高性能合并搜索的自动化流程。该数据集收录了Hub的配置状态快照,无需手动打开配置文件即可获取相关信息。
python
import polars as pl
# 请使用例如 `huggingface-cli login` 登录以访问本数据集
df = pl.read_parquet('hf://datasets/louisbrulenaudet/mergekit-configs/data/raw-00000-of-00001.parquet')
result = (
df.groupby(
[
"architectures",
"hidden_size",
"model_type",
"intermediate_size"
]
).agg(
pl.struct([pl.col("id")]).alias("models")
)
)
## 引用与作者
若您在研究中使用本数据集,请遵循以下BibTeX引用格式。
BibTeX
@misc{HFforLegal2024,
author = {Louis Brulé Naudet},
title = {MergeKit-configs: access all Hub architectures and automate your model merging process},
year = {2024}
howpublished = {url{https://huggingface.co/datasets/louisbrulenaudet/mergekit-configs}},
}
## 反馈
如有任何反馈,请联系[louisbrulenaudet@icloud.com](mailto:louisbrulenaudet@icloud.com).
提供机构:
maas
创建时间:
2025-10-13



