Upload basic_inference_llama_2_dolphin.ipynb

assets/basic_inference_llama_2_dolphin.ipynb

@@ -0,0 +1,1311 @@
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+   "metadata": {
+    "id": "761319ec-18e8-46c5-b7d6-bfdabc892e38"
+   },
+   "source": [
+    "## Post-process a finetuned LLM\n",
+    "\n",
+    "Test and upload a finetuned language model"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "00e6173c-597b-4eb0-8275-bab2c62d4d48",
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
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+    "outputId": "290cab53-6854-41de-a1fa-e0d174adbf59"
+   },
+   "outputs": [],
+   "source": [
+    "!pip install -q -U huggingface_hub peft transformers torch accelerate bitsandbytes"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "7d9e47e4-3adf-4aa4-910c-9f75eb213420",
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 145,
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+    "outputId": "8bb2c7e5-c0ee-4715-bba9-725a531d3ea5"
+   },
+   "outputs": [],
+   "source": [
+    "from huggingface_hub import notebook_login\n",
+    "\n",
+    "notebook_login()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "25376737-3af9-4382-9240-9e94050c8ae7",
+   "metadata": {
+    "id": "25376737-3af9-4382-9240-9e94050c8ae7"
+   },
+   "outputs": [],
+   "source": [
+    "!git config --global credential.helper store"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e24d7ddd-044f-4739-8b01-5a1b187150f5",
+   "metadata": {
+    "id": "e24d7ddd-044f-4739-8b01-5a1b187150f5"
+   },
+   "source": [
+    "## Setup"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "bfeb06bd-96d9-4db0-81ee-1053104f915c",
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "bfeb06bd-96d9-4db0-81ee-1053104f915c",
+    "outputId": "bbba2467-7171-497f-e66e-2bcb6237c183"
+   },
+   "outputs": [],
+   "source": [
+    "!nvidia-smi"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c68a3bba-f374-4ed6-acb6-ebedeb6e29be",
+   "metadata": {
+    "id": "c68a3bba-f374-4ed6-acb6-ebedeb6e29be"
+   },
+   "source": [
+    "## Loss curve\n",
+    "\n",
+    "During training, the model converged nicely as follows:\n",
+    "\n",
+    "![image](https://raw.githubusercontent.com/daniel-furman/sft-demos/main/assets/jul_24_23_1_14_00_log_loss_curves_llama-2-70b-dolphin.png)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d6076740-c324-49a9-841e-30b4878d208b",
+   "metadata": {
+    "id": "d6076740-c324-49a9-841e-30b4878d208b"
+   },
+   "source": [
+    "## Basic usage\n",
+    "\n",
+    "With a supervised finetuned (sft) model in hand, we can test it on some basic prompts and then upload it to the Hugging Face hub either as a public or private model repo, depending on the use case."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "AsrAO-TL25pN",
+   "metadata": {
+    "id": "AsrAO-TL25pN"
+   },
+   "outputs": [],
+   "source": [
+    "import torch\n",
+    "from peft import PeftModel, PeftConfig\n",
+    "from transformers import (\n",
+    "    AutoModelForCausalLM,\n",
+    "    AutoTokenizer,\n",
+    "    BitsAndBytesConfig,\n",
+    "    pipeline,\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "6b17e2d0-b482-4ebd-a830-325d98318f70",
+   "metadata": {
+    "id": "6b17e2d0-b482-4ebd-a830-325d98318f70"
+   },
+   "outputs": [],
+   "source": [
+    "peft_model_id = \"dfurman/llama-2-13b-dolphin-peft\"\n",
+    "config = PeftConfig.from_pretrained(peft_model_id)\n",
+    "\n",
+    "bnb_config = BitsAndBytesConfig(\n",
+    "    load_in_4bit=True,\n",
+    "    bnb_4bit_quant_type=\"nf4\",\n",
+    "    bnb_4bit_compute_dtype=torch.bfloat16,\n",
+    ")\n",
+    "\n",
+    "model = AutoModelForCausalLM.from_pretrained(\n",
+    "    config.base_model_name_or_path,\n",
+    "    quantization_config=bnb_config,\n",
+    "    use_auth_token=True,\n",
+    "    device_map=\"auto\",\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "FE_Tdkin3Whb",
+   "metadata": {
+    "id": "FE_Tdkin3Whb"
+   },
+   "outputs": [],
+   "source": [
+    "# Load the tokenizer\n",
+    "tokenizer = AutoTokenizer.from_pretrained(config.base_model_name_or_path, use_fast=True)\n",
+    "tokenizer.pad_token = tokenizer.eos_token\n",
+    "\n",
+    "# Load the Lora model\n",
+    "model = PeftModel.from_pretrained(model, peft_model_id)\n",
+    "\n",
+    "# Prompt formatter\n",
+    "format_template = \"You are a helpful assistant. {query}\\n\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "b93b4abc-50e6-4308-8bfb-dfd164aef43f",
+   "metadata": {
+    "id": "b93b4abc-50e6-4308-8bfb-dfd164aef43f"
+   },
+   "outputs": [],
+   "source": [
+    "model"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "136794be-1cf3-4478-90df-61507179f076",
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "136794be-1cf3-4478-90df-61507179f076",
+    "outputId": "786629c0-3f80-47bc-b853-a2beecf22c88"
+   },
+   "outputs": [],
+   "source": [
+    "free_in_GB = int(torch.cuda.mem_get_info()[0] / 1024**3)\n",
+    "max_memory = f\"{free_in_GB-2}GB\"\n",
+    "n_gpus = torch.cuda.device_count()\n",
+    "max_memory = {i: max_memory for i in range(n_gpus)}\n",
+    "print(\"max memory: \", max_memory)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "5g-JzwDH3NHi",
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 35
+    },
+    "id": "5g-JzwDH3NHi",
+    "outputId": "de3d6611-7771-44d9-8dc4-5dfa72800bda"
+   },
+   "outputs": [],
+   "source": [
+    "# First, format the prompt\n",
+    "query = \"Tell me a recipe for vegan banana bread.\"\n",
+    "prompt = format_template.format(query=query)\n",
+    "prompt"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "p-v89cpL7nyN",
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "p-v89cpL7nyN",
+    "outputId": "6874c921-ab46-4613-c26e-ce0e29f06f42"
+   },
+   "outputs": [],
+   "source": [
+    "# Inference can be done using model.generate\n",
+    "print(\"\\n\\n*** Generate:\")\n",
+    "\n",
+    "input_ids = tokenizer(prompt, return_tensors=\"pt\").input_ids.cuda()\n",
+    "with torch.autocast(\"cuda\", dtype=torch.bfloat16):\n",
+    "    output = model.generate(\n",
+    "        input_ids=input_ids,\n",
+    "        max_new_tokens=512,\n",
+    "        do_sample=True,\n",
+    "        temperature=0.7,\n",
+    "        return_dict_in_generate=True,\n",
+    "        eos_token_id=tokenizer.eos_token_id,\n",
+    "        pad_token_id=tokenizer.pad_token_id,\n",
+    "        repetition_penalty=1.2,\n",
+    "    )\n",
+    "\n",
+    "print(tokenizer.decode(output[\"sequences\"][0], skip_special_tokens=True))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1vPU1_9E93Fp",
+   "metadata": {
+    "id": "1vPU1_9E93Fp"
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "GiuA0h8779pf",
+   "metadata": {
+    "id": "GiuA0h8779pf"
+   },
+   "outputs": [],
+   "source": []
+  }
+ ],
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+  "accelerator": "GPU",
+  "colab": {
+   "gpuType": "A100",
+   "machine_shape": "hm",
+   "provenance": []
+  },
+  "interpreter": {
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+  },
+  "kernelspec": {
+   "display_name": "Python 3",
+   "name": "python3"
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+  "language_info": {
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