---
dataset_info:
  features:
  - name: id
    dtype: string
  - name: author
    dtype: string
  - name: sha
    dtype: 'null'
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    dtype: timestamp[us, tz=UTC]
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  - name: max_position_embeddings
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  - name: model_type
    dtype: string
  - name: num_attention_heads
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  - name: num_hidden_layers
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    dtype: int64
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    dtype: float64
  - name: rope_theta
    dtype: float64
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    dtype: int64
  - name: tie_word_embeddings
    dtype: bool
  - name: torch_dtype
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    struct:
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      dtype: float64
    - name: original_max_position_embeddings
      dtype: float64
  splits:
  - name: raw
    num_bytes: 70119636
    num_examples: 129379
  download_size: 9132674
  dataset_size: 70119636
configs:
- config_name: default
  data_files:
  - split: raw
    path: data/raw-*
license: apache-2.0
task_categories:
- question-answering
language:
- en
- fr
tags:
- merge
- mergekit
- configs
- code
- automation
pretty_name: 'mergekit-configs: access all Hub architecture'
size_categories:
- 100K<n<1M
---

## 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).