Datasets:
metadata
dataset_info:
features:
- name: id
dtype: string
- name: author
dtype: string
- name: sha
dtype: 'null'
- name: created_at
dtype: timestamp[us, tz=UTC]
- name: last_modified
dtype: 'null'
- name: disabled
dtype: 'null'
- name: downloads
dtype: int64
- name: downloads_all_time
dtype: 'null'
- name: gated
dtype: bool
- name: gguf
dtype: 'null'
- name: inference
dtype: 'null'
- name: likes
dtype: int64
- name: library_name
dtype: string
- name: tags
sequence: string
- name: pipeline_tag
dtype: string
- name: mask_token
dtype: 'null'
- name: model_index
dtype: 'null'
- name: trending_score
dtype: int64
- name: architectures
sequence: string
- name: bos_token_id
dtype: int64
- name: eos_token_id
dtype: int64
- name: hidden_act
dtype: string
- name: hidden_size
dtype: int64
- name: initializer_range
dtype: float64
- name: intermediate_size
dtype: int64
- name: max_position_embeddings
dtype: int64
- name: model_type
dtype: string
- name: num_attention_heads
dtype: int64
- name: num_hidden_layers
dtype: int64
- name: num_key_value_heads
dtype: int64
- name: rms_norm_eps
dtype: float64
- name: rope_theta
dtype: float64
- name: sliding_window
dtype: int64
- name: tie_word_embeddings
dtype: bool
- name: torch_dtype
dtype: string
- name: transformers_version
dtype: string
- name: use_cache
dtype: bool
- name: vocab_size
dtype: int64
- name: attention_bias
dtype: bool
- name: attention_dropout
dtype: float64
- name: head_dim
dtype: int64
- name: mlp_bias
dtype: bool
- name: pretraining_tp
dtype: int64
- name: rope_scaling
struct:
- name: factor
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
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.
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.
@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.