import pathlib import tempfile from typing import Generator import gradio as gr import huggingface_hub import torch import yaml from gradio_logsview.logsview import LogsView, LogsViewRunner from mergekit.common import parse_kmb from mergekit.config import MergeConfiguration from mergekit.merge import run_merge from mergekit.options import MergeOptions has_gpu = torch.cuda.is_available() merge_options = ( MergeOptions( copy_tokenizer=True, cuda=True, low_cpu_memory=True, write_model_card=True, ) if has_gpu else MergeOptions( allow_crimes=True, out_shard_size=parse_kmb("1B"), lazy_unpickle=True, write_model_card=True, ) ) ## This Space is heavily inspired by LazyMergeKit by Maxime Labonne ## https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb MARKDOWN_DESCRIPTION = """ # mergekit-gui The fastest way to perform a model merge 🔥 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. """ MARKDOWN_ARTICLE = """ ___ ## Merge Configuration [Mergekit](https://github.com/arcee-ai/mergekit) configurations are YAML documents specifying the operations to perform in order to produce your merged model. Below are the primary elements of a configuration file: - `merge_method`: Specifies the method to use for merging models. See [Merge Methods](https://github.com/arcee-ai/mergekit#merge-methods) for a list. - `slices`: Defines slices of layers from different models to be used. This field is mutually exclusive with `models`. - `models`: Defines entire models to be used for merging. This field is mutually exclusive with `slices`. - `base_model`: Specifies the base model used in some merging methods. - `parameters`: Holds various parameters such as weights and densities, which can also be specified at different levels of the configuration. - `dtype`: Specifies the data type used for the merging operation. - `tokenizer_source`: Determines how to construct a tokenizer for the merged model. ## Merge Methods A quick overview of the currently supported merge methods: | Method | `merge_method` value | Multi-Model | Uses base model | | -------------------------------------------------------------------------------------------- | -------------------- | ----------- | --------------- | | Linear ([Model Soups](https://arxiv.org/abs/2203.05482)) | `linear` | ✅ | ❌ | | SLERP | `slerp` | ❌ | ✅ | | [Task Arithmetic](https://arxiv.org/abs/2212.04089) | `task_arithmetic` | ✅ | ✅ | | [TIES](https://arxiv.org/abs/2306.01708) | `ties` | ✅ | ✅ | | [DARE](https://arxiv.org/abs/2311.03099) [TIES](https://arxiv.org/abs/2306.01708) | `dare_ties` | ✅ | ✅ | | [DARE](https://arxiv.org/abs/2311.03099) [Task Arithmetic](https://arxiv.org/abs/2212.04089) | `dare_linear` | ✅ | ✅ | | Passthrough | `passthrough` | ❌ | ❌ | | [Model Stock](https://arxiv.org/abs/2403.19522) | `model_stock` | ✅ | ✅ | """ examples = [[str(f)] for f in pathlib.Path("examples").glob("*.yml")] def merge( example_filename: str, yaml_config: str, hf_token: str | None, repo_name: str | None ) -> Generator[str, None, None]: if not yaml_config: raise gr.Error("Empty yaml, pick an example below") try: merge_config = MergeConfiguration.model_validate(yaml.safe_load(yaml_config)) except Exception as e: raise gr.Error(f"Invalid yaml {e}") runner = LogsViewRunner() with tempfile.TemporaryDirectory() as tmpdirname: tmpdir = pathlib.Path(tmpdirname) merged_path = tmpdir / "merged" merged_path.mkdir(parents=True, exist_ok=True) config_path = merged_path / "config.yaml" config_path.write_text(yaml_config) yield runner.log(f"Merge configuration saved in {config_path}") if token is not None and repo_name == "": name = "-".join( model.model.path for model in merge_config.referenced_models() ) repo_name = f"mergekit-{merge_config.merge_method}-{name}".replace("/", "-").strip("-") if len(repo_name) > 50: repo_name = repo_name[:25] + "-etc-" + repo_name[25:] runner.log(f"Will save merged in {repo_name} once process is done.") if token is None: yield runner.log( "No token provided, merge will run in dry-run mode (no upload at the end of the process)." ) # Taken from https://github.com/arcee-ai/mergekit/blob/main/mergekit/scripts/run_yaml.py yield from runner.run_python( run_merge, merge_config=merge_config, out_path=str(merged_path), options=merge_options, config_source=str(config_path), ) if runner.exit_code != 0: yield runner.log("Merge failed. Terminating here. No model has been uploaded.") return if hf_token is not None: api = huggingface_hub.HfApi(token=hf_token) yield runner.log("Creating repo") repo_url = api.create_repo(repo_name, exist_ok=True) yield runner.log(f"Repo created: {repo_url}") folder_url = api.upload_folder( repo_id=repo_url.repo_id, folder_path=merged_path ) yield runner.log(f"Model successfully uploaded to {folder_url}") with gr.Blocks() as demo: gr.Markdown(MARKDOWN_DESCRIPTION) with gr.Row(): filename = gr.Textbox(visible=False, label="filename") config = gr.Code(language="yaml", lines=10, label="config.yaml") with gr.Column(): token = gr.Textbox( lines=1, label="HF Write Token", info="https://hf.co/settings/token", type="password", placeholder="optional, will not upload merge if empty (dry-run)", ) repo_name = gr.Textbox( lines=1, label="Repo name", placeholder="optional, will create a random name if empty", ) button = gr.Button("Merge", variant="primary") logs = LogsView() gr.Examples( examples, fn=lambda s: (s,), run_on_click=True, label="Examples", inputs=[filename], outputs=[config], ) gr.Markdown(MARKDOWN_ARTICLE) button.click(fn=merge, inputs=[filename, config, token, repo_name], outputs=[logs]) demo.queue(default_concurrency_limit=1).launch()