diff --git "a/LazyMergekit.ipynb" "b/LazyMergekit.ipynb"
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-{
- "nbformat": 4,
- "nbformat_minor": 0,
- "metadata": {
- "colab": {
- "provenance": [],
- "gpuType": "T4"
- },
- "kernelspec": {
- "name": "python3",
- "display_name": "Python 3"
- },
- "language_info": {
- "name": "python"
- },
- "accelerator": "GPU"
- },
- "cells": [
- {
- "cell_type": "markdown",
- "source": [
- "# 🥱 LazyMergekit\n",
- "\n",
- "> 🗣️ [Large Language Model Course](https://github.com/mlabonne/llm-course)\n",
- "\n",
- "❤️ Created by [@maximelabonne](https://twitter.com/maximelabonne).\n",
- "\n",
- "This notebook allows you to easily merge multiple models using [mergekit](https://github.com/cg123/mergekit). To evaluate your merges, see [🧐 LLM AutoEval](https://colab.research.google.com/drive/1Igs3WZuXAIv9X0vwqiE90QlEPys8e8Oa?usp=sharing#scrollTo=elyxjYI_rY5W).\n",
- "\n",
- "*Special thanks to [@cg123](https://github.com/cg123) for this library and [@mrfakename](https://gist.github.com/fakerybakery) who told me about sharding (see his [Gist](https://gist.github.com/fakerybakery/d30a4d31b4f914757c1381166b9c683b)).*"
- ],
- "metadata": {
- "id": "1Wq4SB9A_9ic"
- }
- },
- {
- "cell_type": "code",
- "source": [
- "MODEL_NAME = \"M-LChat-7b-2\"\n",
- "yaml_config = \"\"\"\n",
- "slices:\n",
- " - sources:\n",
- " - model: openchat/openchat-3.5-0106\n",
- " layer_range: [0, 32]\n",
- " - model: FuseAI/FuseChat-7B-VaRM\n",
- " layer_range: [0, 32]\n",
- " - model: Nexusflow/Starling-LM-7B-beta\n",
- " layer_range: [0, 32]\n",
- "merge_method: slerp\n",
- "base_model: OpenPipe/mistral-ft-optimized-1218\n",
- "parameters:\n",
- " t:\n",
- " - filter: self_attn\n",
- " value: [0, 0.5, 0.3, 0.7, 1]\n",
- " - filter: mlp\n",
- " value: [1, 0.5, 0.7, 0.3, 0]\n",
- " - value: 0.5\n",
- "dtype: bfloat16\n",
- "\"\"\""
- ],
- "metadata": {
- "id": "LGd7jlfCpNcg"
- },
- "execution_count": 1,
- "outputs": []
- },
- {
- "cell_type": "code",
- "source": [
- "# @title ## Run merge\n",
- "\n",
- "# @markdown ### Runtime type\n",
- "# @markdown Select your runtime (CPU, High RAM, GPU)\n",
- "\n",
- "runtime = \"GPU\" # @param [\"CPU\", \"CPU + High-RAM\", \"GPU\"]\n",
- "\n",
- "# @markdown ### Mergekit arguments\n",
- "# @markdown Use the `main` branch by default, [`mixtral`](https://github.com/cg123/mergekit/blob/mixtral/moe.md) if you want to create a Mixture of Experts.\n",
- "\n",
- "branch = \"main\" # @param [\"main\", \"mixtral\"]\n",
- "trust_remote_code = False # @param {type:\"boolean\"}\n",
- "\n",
- "# Install mergekit\n",
- "if branch == \"main\":\n",
- " !git clone https://github.com/arcee-ai/mergekit.git\n",
- " !cd mergekit && pip install -qqq -e . --progress-bar off\n",
- "elif branch == \"mixtral\":\n",
- " !git clone -b mixtral https://github.com/arcee-ai/mergekit.git\n",
- " !cd mergekit && pip install -qqq -e . --progress-bar off\n",
- " !pip install -qqq -U transformers --progress-bar off\n",
- "\n",
- "# Save config as yaml file\n",
- "with open('config.yaml', 'w', encoding=\"utf-8\") as f:\n",
- " f.write(yaml_config)\n",
- "\n",
- "# Base CLI\n",
- "if branch == \"main\":\n",
- " cli = \"mergekit-yaml config.yaml merge --copy-tokenizer\"\n",
- "elif branch == \"mixtral\":\n",
- " cli = \"mergekit-moe config.yaml merge --copy-tokenizer\"\n",
- "\n",
- "# Additional arguments\n",
- "if runtime == \"CPU\":\n",
- " cli += \" --allow-crimes --out-shard-size 1B --lazy-unpickle\"\n",
- "elif runtime == \"GPU\":\n",
- " cli += \" --cuda --low-cpu-memory\"\n",
- "if trust_remote_code:\n",
- " cli += \" --trust-remote-code\"\n",
- "\n",
- "print(cli)\n",
- "\n",
- "# Merge models\n",
- "!{cli}"
- ],
- "metadata": {
- "id": "d5mYzDo1q96y",
- "outputId": "496ae72f-522b-439b-ac01-0930b11d897d",
- "colab": {
- "base_uri": "https://localhost:8080/"
- }
- },
- "execution_count": 2,
- "outputs": [
- {
- "output_type": "stream",
- "name": "stdout",
- "text": [
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- "Fetching 12 files: 25% 3/12 [01:01<03:03, 20.42s/it]\n",
- "Warmup loader cache: 75% 3/4 [09:42<03:14, 194.30s/it]\n",
- "Traceback (most recent call last):\n",
- " File \"/usr/local/bin/mergekit-yaml\", line 8, in <module>\n",
- " sys.exit(main())\n",
- " File \"/usr/local/lib/python3.10/dist-packages/click/core.py\", line 1157, in __call__\n",
- " return self.main(*args, **kwargs)\n",
- " File \"/usr/local/lib/python3.10/dist-packages/click/core.py\", line 1078, in main\n",
- " rv = self.invoke(ctx)\n",
- " File \"/usr/local/lib/python3.10/dist-packages/click/core.py\", line 1434, in invoke\n",
- " return ctx.invoke(self.callback, **ctx.params)\n",
- " File \"/usr/local/lib/python3.10/dist-packages/click/core.py\", line 783, in invoke\n",
- " return __callback(*args, **kwargs)\n",
- " File \"/content/mergekit/mergekit/options.py\", line 78, in wrapper\n",
- " f(*args, **kwargs)\n",
- " File \"/content/mergekit/mergekit/scripts/run_yaml.py\", line 47, in main\n",
- " run_merge(\n",
- " File \"/content/mergekit/mergekit/merge.py\", line 69, in run_merge\n",
- " loader_cache.get(model)\n",
- " File \"/content/mergekit/mergekit/io/tasks.py\", line 34, in get\n",
- " self.loaders[model] = merged.lazy_loader(cache_dir=self.hf_cache_dir)\n",
- " File \"/content/mergekit/mergekit/common.py\", line 157, in lazy_loader\n",
- " self.tensor_index(cache_dir),\n",
- " File \"/content/mergekit/mergekit/common.py\", line 144, in tensor_index\n",
- " path = huggingface_hub.snapshot_download(\n",
- " File \"/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_validators.py\", line 118, in _inner_fn\n",
- " return fn(*args, **kwargs)\n",
- " File \"/usr/local/lib/python3.10/dist-packages/huggingface_hub/_snapshot_download.py\", line 308, in snapshot_download\n",
- " thread_map(\n",
- " File \"/usr/local/lib/python3.10/dist-packages/tqdm/contrib/concurrent.py\", line 69, in thread_map\n",
- " return _executor_map(ThreadPoolExecutor, fn, *iterables, **tqdm_kwargs)\n",
- " File \"/usr/local/lib/python3.10/dist-packages/tqdm/contrib/concurrent.py\", line 51, in _executor_map\n",
- " return list(tqdm_class(ex.map(fn, *iterables, chunksize=chunksize), **kwargs))\n",
- " File \"/usr/local/lib/python3.10/dist-packages/tqdm/std.py\", line 1181, in __iter__\n",
- " for obj in iterable:\n",
- " File \"/usr/lib/python3.10/concurrent/futures/_base.py\", line 621, in result_iterator\n",
- " yield _result_or_cancel(fs.pop())\n",
- " File \"/usr/lib/python3.10/concurrent/futures/_base.py\", line 319, in _result_or_cancel\n",
- " return fut.result(timeout)\n",
- " File \"/usr/lib/python3.10/concurrent/futures/_base.py\", line 458, in result\n",
- " return self.__get_result()\n",
- " File \"/usr/lib/python3.10/concurrent/futures/_base.py\", line 403, in __get_result\n",
- " raise self._exception\n",
- " File \"/usr/lib/python3.10/concurrent/futures/thread.py\", line 58, in run\n",
- " result = self.fn(*self.args, **self.kwargs)\n",
- " File \"/usr/local/lib/python3.10/dist-packages/huggingface_hub/_snapshot_download.py\", line 283, in _inner_hf_hub_download\n",
- " return hf_hub_download(\n",
- " File \"/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_validators.py\", line 118, in _inner_fn\n",
- " return fn(*args, **kwargs)\n",
- " File \"/usr/local/lib/python3.10/dist-packages/huggingface_hub/file_download.py\", line 1457, in hf_hub_download\n",
- " http_get(\n",
- " File \"/usr/local/lib/python3.10/dist-packages/huggingface_hub/file_download.py\", line 527, in http_get\n",
- " temp_file.write(chunk)\n",
- " File \"/usr/lib/python3.10/tempfile.py\", line 622, in func_wrapper\n",
- " return func(*args, **kwargs)\n",
- "OSError: [Errno 28] No space left on device\n"
- ]
- }
- ]
- },
- {
- "cell_type": "code",
- "source": [
- "# @title ## Upload model to Hugging Face { display-mode: \"form\" }\n",
- "# @markdown Enter your HF username and the name of Colab secret that stores your [Hugging Face access token](https://huggingface.co/settings/tokens).\n",
- "username = 'Artples' # @param {type:\"string\"}\n",
- "token = 'HF_TOKEN' # @param {type:\"string\"}\n",
- "license = \"apache-2.0\" # @param [\"apache-2.0\", \"cc-by-nc-4.0\", \"mit\", \"openrail\"] {allow-input: true}\n",
- "\n",
- "!pip install -qU huggingface_hub\n",
- "\n",
- "import yaml\n",
- "\n",
- "from huggingface_hub import ModelCard, ModelCardData, HfApi\n",
- "from google.colab import userdata\n",
- "from jinja2 import Template\n",
- "\n",
- "if branch == \"main\":\n",
- " template_text = \"\"\"\n",
- "---\n",
- "license: {{ license }}\n",
- "base_model:\n",
- "{%- for model in models %}\n",
- " - {{ model }}\n",
- "{%- endfor %}\n",
- "tags:\n",
- "- merge\n",
- "- mergekit\n",
- "- lazymergekit\n",
- "{%- for model in models %}\n",
- "- {{ model }}\n",
- "{%- endfor %}\n",
- "---\n",
- "\n",
- "# {{ model_name }}\n",
- "\n",
- "{{ model_name }} is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):\n",
- "\n",
- "{%- for model in models %}\n",
- "* [{{ model }}](https://huggingface.co/{{ model }})\n",
- "{%- endfor %}\n",
- "\n",
- "## 🧩 Configuration\n",
- "\n",
- "```yaml\n",
- "{{- yaml_config -}}\n",
- "```\n",
- "\n",
- "## 💻 Usage\n",
- "\n",
- "```python\n",
- "!pip install -qU transformers accelerate\n",
- "\n",
- "from transformers import AutoTokenizer\n",
- "import transformers\n",
- "import torch\n",
- "\n",
- "model = \"{{ username }}/{{ model_name }}\"\n",
- "messages = [{\"role\": \"user\", \"content\": \"What is a large language model?\"}]\n",
- "\n",
- "tokenizer = AutoTokenizer.from_pretrained(model)\n",
- "prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)\n",
- "pipeline = transformers.pipeline(\n",
- " \"text-generation\",\n",
- " model=model,\n",
- " torch_dtype=torch.float16,\n",
- " device_map=\"auto\",\n",
- ")\n",
- "\n",
- "outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)\n",
- "print(outputs[0][\"generated_text\"])\n",
- "```\n",
- "\"\"\"\n",
- "\n",
- " # Create a Jinja template object\n",
- " jinja_template = Template(template_text.strip())\n",
- "\n",
- " # Get list of models from config\n",
- " data = yaml.safe_load(yaml_config)\n",
- " if \"models\" in data:\n",
- " models = [data[\"models\"][i][\"model\"] for i in range(len(data[\"models\"])) if \"parameters\" in data[\"models\"][i]]\n",
- " elif \"parameters\" in data:\n",
- " models = [data[\"slices\"][0][\"sources\"][i][\"model\"] for i in range(len(data[\"slices\"][0][\"sources\"]))]\n",
- " elif \"slices\" in data:\n",
- " models = [data[\"slices\"][i][\"sources\"][0][\"model\"] for i in range(len(data[\"slices\"]))]\n",
- " else:\n",
- " raise Exception(\"No models or slices found in yaml config\")\n",
- "\n",
- " # Fill the template\n",
- " content = jinja_template.render(\n",
- " model_name=MODEL_NAME,\n",
- " models=models,\n",
- " yaml_config=yaml_config,\n",
- " username=username,\n",
- " )\n",
- "\n",
- "elif branch == \"mixtral\":\n",
- " template_text = \"\"\"\n",
- "---\n",
- "license: {{ license }}\n",
- "base_model:\n",
- "{%- for model in models %}\n",
- " - {{ model }}\n",
- "{%- endfor %}\n",
- "tags:\n",
- "- moe\n",
- "- frankenmoe\n",
- "- merge\n",
- "- mergekit\n",
- "- lazymergekit\n",
- "{%- for model in models %}\n",
- "- {{ model }}\n",
- "{%- endfor %}\n",
- "---\n",
- "\n",
- "# {{ model_name }}\n",
- "\n",
- "{{ model_name }} is a Mixture of Experts (MoE) made with the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):\n",
- "\n",
- "{%- for model in models %}\n",
- "* [{{ model }}](https://huggingface.co/{{ model }})\n",
- "{%- endfor %}\n",
- "\n",
- "## 🧩 Configuration\n",
- "\n",
- "```yaml\n",
- "{{- yaml_config -}}\n",
- "```\n",
- "\n",
- "## 💻 Usage\n",
- "\n",
- "```python\n",
- "!pip install -qU transformers bitsandbytes accelerate\n",
- "\n",
- "from transformers import AutoTokenizer\n",
- "import transformers\n",
- "import torch\n",
- "\n",
- "model = \"{{ username }}/{{ model_name }}\"\n",
- "\n",
- "tokenizer = AutoTokenizer.from_pretrained(model)\n",
- "pipeline = transformers.pipeline(\n",
- " \"text-generation\",\n",
- " model=model,\n",
- " model_kwargs={\"torch_dtype\": torch.float16, \"load_in_4bit\": True},\n",
- ")\n",
- "\n",
- "messages = [{\"role\": \"user\", \"content\": \"Explain what a Mixture of Experts is in less than 100 words.\"}]\n",
- "prompt = pipeline.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)\n",
- "outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)\n",
- "print(outputs[0][\"generated_text\"])\n",
- "```\n",
- "\"\"\"\n",
- "\n",
- " # Create a Jinja template object\n",
- " jinja_template = Template(template_text.strip())\n",
- "\n",
- " # Fill the template\n",
- " data = yaml.safe_load(yaml_config)\n",
- " models = [model['source_model'] for model in data['experts']]\n",
- "\n",
- " content = jinja_template.render(\n",
- " model_name=MODEL_NAME,\n",
- " models=models,\n",
- " yaml_config=yaml_config,\n",
- " username=username,\n",
- " license=license\n",
- " )\n",
- "\n",
- "# Save the model card\n",
- "card = ModelCard(content)\n",
- "card.save('merge/README.md')\n",
- "\n",
- "# Defined in the secrets tab in Google Colab\n",
- "api = HfApi(token=userdata.get(token))\n",
- "\n",
- "# Upload merge folder\n",
- "api.create_repo(\n",
- " repo_id=f\"{username}/{MODEL_NAME}\",\n",
- " repo_type=\"model\",\n",
- " exist_ok=True,\n",
- ")\n",
- "api.upload_folder(\n",
- " repo_id=f\"{username}/{MODEL_NAME}\",\n",
- " folder_path=\"merge\",\n",
- ")"
- ],
- "metadata": {
- "id": "ik0V0dF55gfU"
- },
- "execution_count": null,
- "outputs": []
- }
- ]
-}
\ No newline at end of file