diff --git "a/LazyMergekit.ipynb" "b/LazyMergekit.ipynb" deleted file mode 100644--- "a/LazyMergekit.ipynb" +++ /dev/null @@ -1,5327 +0,0 @@ -{ - "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", - 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" 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