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import pathlib |
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import tempfile |
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from typing import Generator |
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import gradio as gr |
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import torch |
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import yaml |
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from gradio_logsview import LogsView |
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has_gpu = torch.cuda.is_available() |
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cli = "mergekit-yaml config.yaml merge --copy-tokenizer" + ( |
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" --cuda --low-cpu-memory" |
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if has_gpu |
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else " --allow-crimes --out-shard-size 1B --lazy-unpickle" |
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) |
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print(cli) |
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MARKDOWN_DESCRIPTION = """ |
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# mergekit-gui |
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The fastest way to perform a model merge π₯ |
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Specify a YAML configuration file (see examples below) and a HF token and this app will perform the merge and upload the merged model to your user profile. |
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""" |
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MARKDOWN_ARTICLE = """ |
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___ |
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## Merge Configuration |
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[Mergekit](https://github.com/arcee-ai/mergekit) configurations are YAML documents specifying the operations to perform in order to produce your merged model. |
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Below are the primary elements of a configuration file: |
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- `merge_method`: Specifies the method to use for merging models. See [Merge Methods](https://github.com/arcee-ai/mergekit#merge-methods) for a list. |
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- `slices`: Defines slices of layers from different models to be used. This field is mutually exclusive with `models`. |
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- `models`: Defines entire models to be used for merging. This field is mutually exclusive with `slices`. |
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- `base_model`: Specifies the base model used in some merging methods. |
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- `parameters`: Holds various parameters such as weights and densities, which can also be specified at different levels of the configuration. |
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- `dtype`: Specifies the data type used for the merging operation. |
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- `tokenizer_source`: Determines how to construct a tokenizer for the merged model. |
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## Merge Methods |
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A quick overview of the currently supported merge methods: |
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| Method | `merge_method` value | Multi-Model | Uses base model | |
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| -------------------------------------------------------------------------------------------- | -------------------- | ----------- | --------------- | |
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| Linear ([Model Soups](https://arxiv.org/abs/2203.05482)) | `linear` | β
| β | |
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| SLERP | `slerp` | β | β
| |
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| [Task Arithmetic](https://arxiv.org/abs/2212.04089) | `task_arithmetic` | β
| β
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| [TIES](https://arxiv.org/abs/2306.01708) | `ties` | β
| β
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| [DARE](https://arxiv.org/abs/2311.03099) [TIES](https://arxiv.org/abs/2306.01708) | `dare_ties` | β
| β
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| [DARE](https://arxiv.org/abs/2311.03099) [Task Arithmetic](https://arxiv.org/abs/2212.04089) | `dare_linear` | β
| β
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| Passthrough | `passthrough` | β | β | |
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| [Model Stock](https://arxiv.org/abs/2403.19522) | `model_stock` | β
| β
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""" |
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examples = [[str(f)] for f in pathlib.Path("examples").glob("*.yml")] |
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def merge( |
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example_filename: str, yaml_config: str, hf_token: str, repo_name: str |
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) -> Generator[str, None, None]: |
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if not yaml_config: |
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raise gr.Error("Empty yaml, pick an example below") |
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try: |
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_ = yaml.safe_load(yaml_config) |
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except Exception as e: |
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raise gr.Error(f"Invalid yaml {e}") |
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with tempfile.TemporaryDirectory() as tmpdirname: |
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tmpdir = pathlib.Path(tmpdirname) |
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config_path = tmpdir / "config.yaml" |
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config_path.write_text(yaml_config) |
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yield from LogsView.run_process(cli.split(), cwd=tmpdir) |
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with gr.Blocks() as demo: |
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gr.Markdown(MARKDOWN_DESCRIPTION) |
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with gr.Row(): |
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filename = gr.Textbox(visible=False, label="filename") |
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config = gr.Code( |
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language="yaml", |
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lines=10, |
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label="config.yaml", |
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) |
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with gr.Column(): |
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token = gr.Textbox( |
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lines=1, |
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label="HF Write Token", |
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info="https://hf.co/settings/token", |
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type="password", |
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placeholder="optional, will not upload merge if empty (dry-run)", |
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) |
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repo_name = gr.Textbox( |
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lines=1, |
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label="Repo name", |
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placeholder="optional, will create a random name if empty", |
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) |
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button = gr.Button("Merge", variant="primary") |
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logs = LogsView() |
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gr.Examples(examples, fn=lambda s: (s,), run_on_click=True, |
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label="Examples", inputs=[filename], outputs=[config]) |
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gr.Markdown(MARKDOWN_ARTICLE) |
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button.click(fn=merge, inputs=[filename, config, token, repo_name], outputs=[logs]) |
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demo.queue(default_concurrency_limit=1).launch() |
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