LLMs/FineTuning_phi-1_5_with_PRFT_LoRA.ipynb

{"cells":[{"cell_type":"markdown","metadata":{},"source":["##  Fine Tuning Phi 1_5 with PEFT and QLoRA\n","\n","# [Link to my Youtube Video Explaining this whole Notebook](https://www.youtube.com/watch?v=J0RbOtLrJhQ&list=PLxqBkZuBynVTzqUQCQFgetR97y1X_1uCI&index=10&ab_channel=Rohan-Paul-AI)\n","\n","[![Imgur](https://imgur.com/ensYOlt.png)](https://www.youtube.com/watch?v=J0RbOtLrJhQ&list=PLxqBkZuBynVTzqUQCQFgetR97y1X_1uCI&index=10&ab_channel=Rohan-Paul-AI)\n","\n"]},{"cell_type":"code","execution_count":1,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"execution":{"iopub.execute_input":"2023-10-05T16:07:37.639436Z","iopub.status.busy":"2023-10-05T16:07:37.639073Z","iopub.status.idle":"2023-10-05T16:07:52.741784Z","shell.execute_reply":"2023-10-05T16:07:52.740692Z","shell.execute_reply.started":"2023-10-05T16:07:37.639411Z"},"id":"Z-jiAReD2env","outputId":"aab817b4-8b11-428f-d1ef-8e125cb73e96","trusted":true},"outputs":[],"source":["!pip install accelerate transformers einops datasets peft bitsandbytes --upgrade"]},{"cell_type":"code","execution_count":2,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":145,"referenced_widgets":["5a9533ffb93347188124118112af6b9e","6db10be3ae0d4b7583c0e60113dea440","acc1272d912c413495f846b211e9d9f3","3fb481a5c7b94475a41b9b08c4952b50","bccf11abbeb24e6fbd702ddb96af9a45","1197df4791284aa1a5b328051e90aea0","a492647ee6db4666927a85bf9b57846f","a38a221405a344e4b6493347d2625432","a367b0a6e55349b4941bdf1a67b119a9","61ce75ea6781491e8a99f0d89b2ef2de","350aa7ba9e194799996b15f2598a2d95","1f29b977a0884c299958176cae769d85","7dcf133c23404718a26efa36d66ae5ef","a9d9395f44d944a7bd53e386b330330c","3def007df18f49978843aa4ee2e654cb","a3c480d9538d4dcfb70567ae34186820","5355435a70f54ec8baeca428dea930d4","d7a8137410e14fa19d73253be261c969","1eb1da5836a14f58917de3b3906702c6","f1dd4109841f4dbe8e20e7a22faf8e7d","fbe254109281479dbe044caa3696723e","f767c83810f54eb1af06694e28068b64","1f9da29335d141339e9e242a1e3e082e","b7cba598a18d4090ac1fff7d6f8e9b4f","53a9110515df48359a28d4f1f4f746f5","3ec11a496f704bc3ae3b9b056d924e15","76aeffc655364b609ef4cf876cbe9af6","252f2cda84eb44c9a5064e52d40f0922","f2f27a61009348f9b283aceeedd06768","c062bf9e73b4449b9d97cfb02734f8cf","01bb1fbc21ec439ab1deae9a59d0be84","627e8c067afe4dc48810faa3a3fb9ba6"]},"execution":{"iopub.execute_input":"2023-10-05T16:08:02.284953Z","iopub.status.busy":"2023-10-05T16:08:02.284581Z","iopub.status.idle":"2023-10-05T16:08:02.290173Z","shell.execute_reply":"2023-10-05T16:08:02.289364Z","shell.execute_reply.started":"2023-10-05T16:08:02.284901Z"},"id":"DdZRaqEg2x5K","outputId":"3a9c6bb0-c076-4f4f-f945-e10272c5c27e","trusted":true},"outputs":[],"source":["# from huggingface_hub import notebook_login\n","\n","# notebook_login()"]},{"cell_type":"code","execution_count":null,"metadata":{"execution":{"iopub.execute_input":"2023-10-05T16:08:02.293636Z","iopub.status.busy":"2023-10-05T16:08:02.292844Z","iopub.status.idle":"2023-10-05T16:08:15.067110Z","shell.execute_reply":"2023-10-05T16:08:15.066239Z","shell.execute_reply.started":"2023-10-05T16:08:02.293605Z"},"id":"X2pEaQ0w8188","trusted":true},"outputs":[],"source":["from peft import PeftModel\n","from transformers import AutoModelForCausalLM\n","import torch\n","from datasets import load_dataset, Dataset\n","from transformers import AutoModelForCausalLM, AutoTokenizer, TrainingArguments, Trainer, DataCollatorForLanguageModeling, BitsAndBytesConfig\n","from peft import LoraConfig, get_peft_model\n","import os"]},{"cell_type":"code","execution_count":4,"metadata":{"execution":{"iopub.execute_input":"2023-10-05T16:08:15.069637Z","iopub.status.busy":"2023-10-05T16:08:15.068414Z","iopub.status.idle":"2023-10-05T16:08:16.573183Z","shell.execute_reply":"2023-10-05T16:08:16.572315Z","shell.execute_reply.started":"2023-10-05T16:08:15.069605Z"},"id":"2x0EnK1X9L9i","trusted":true},"outputs":[{"name":"stderr","output_type":"stream","text":["Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.\n"]}],"source":["tokenizer = AutoTokenizer.from_pretrained(\"microsoft/phi-1_5\", trust_remote_code=True)\n","\n","tokenizer.pad_token = tokenizer.eos_token"]},{"cell_type":"code","execution_count":5,"metadata":{"execution":{"iopub.execute_input":"2023-10-05T16:08:16.575290Z","iopub.status.busy":"2023-10-05T16:08:16.574632Z","iopub.status.idle":"2023-10-05T16:08:42.343596Z","shell.execute_reply":"2023-10-05T16:08:42.342759Z","shell.execute_reply.started":"2023-10-05T16:08:16.575258Z"},"id":"q29CmvRzA996","trusted":true},"outputs":[],"source":["bnb_config = BitsAndBytesConfig(\n","    load_in_4bit=True,\n","    bnb_4bit_use_double_quant=True,\n","    bnb_4bit_quant_type=\"nf4\",\n","    bnb_4bit_compute_dtype=torch.float16\n",")\n","\n","model = AutoModelForCausalLM.from_pretrained(\n","    \"microsoft/phi-1_5\",\n","    device_map={\"\":0},\n","    trust_remote_code=True,\n","    quantization_config=bnb_config\n",")"]},{"cell_type":"code","execution_count":6,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"execution":{"iopub.execute_input":"2023-10-05T16:08:42.345373Z","iopub.status.busy":"2023-10-05T16:08:42.345038Z","iopub.status.idle":"2023-10-05T16:08:42.349369Z","shell.execute_reply":"2023-10-05T16:08:42.348495Z","shell.execute_reply.started":"2023-10-05T16:08:42.345342Z"},"id":"M75zCiGwBM1q","outputId":"3ed2266a-32e9-4fbb-ca95-6a70b39cacb8","trusted":true},"outputs":[],"source":["model"]},{"cell_type":"markdown","metadata":{},"source":["## A little hack to make `get_peft_model()` method faster by avoiding `kaiming_uniform` initialization"]},{"cell_type":"code","execution_count":7,"metadata":{},"outputs":[],"source":["from bitsandbytes.nn.modules import Linear8bitLt, Linear4bit\n","import torch.nn.init as init  # Importing the init module from PyTorch\n","import bitsandbytes as bnb\n","from contextlib import contextmanager\n","\n","def noop (x=None, *args, **kwargs):\n","    \"Do nothing\"\n","    return x\n","\n","@contextmanager\n","def no_kaiming():\n","    old_iku = init.kaiming_uniform_\n","    init.kaiming_uniform_ = noop\n","    try: yield\n","    finally: init.kaiming_uniform_ = old_iku\n","\n","_old_8init = Linear8bitLt.__init__\n","_old_4init = Linear4bit.__init__\n","\n","def _new_4init(self, input_features, output_features, bias=True,\n","               device=None, **kwargs):\n","    with no_kaiming():\n","        return _old_4init(self, input_features, output_features, bias=bias,\n","                          device=device, **kwargs)\n","\n","\n","\n","def _new_8init(self, input_features, output_features, bias=True, has_fp16_weights=True,\n","              memory_efficient_backward=False, threshold=0.0, index=None, device=None):\n","    with no_kaiming():\n","        return _old_8init(self, input_features, output_features, bias=bias, has_fp16_weights=has_fp16_weights,\n","                          memory_efficient_backward=memory_efficient_backward, threshold=threshold, index=index, device=device)\n","\n","Linear8bitLt.__init__ = _new_8init\n","Linear4bit.__init__ = _new_4init"]},{"cell_type":"code","execution_count":8,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"execution":{"iopub.execute_input":"2023-10-05T16:08:42.351464Z","iopub.status.busy":"2023-10-05T16:08:42.350623Z","iopub.status.idle":"2023-10-05T16:08:45.749460Z","shell.execute_reply":"2023-10-05T16:08:45.748537Z","shell.execute_reply.started":"2023-10-05T16:08:42.351434Z"},"id":"MVSrZLrUBegg","outputId":"faabbe70-48f2-45c6-d30c-bc7dcdccde47","trusted":true},"outputs":[{"name":"stdout","output_type":"stream","text":["trainable params: 4,718,592 || all params: 1,422,989,312 || trainable%: 0.3315971497613047\n"]}],"source":["lora_config = LoraConfig(\n","    r=16,\n","    lora_alpha=16,\n","    target_modules=[\"Wqkv\", \"out_proj\"],\n","    lora_dropout=0.05,\n","    bias=\"none\",\n","    task_type=\"CAUSAL_LM\"\n",")\n","\n","model = get_peft_model(model, lora_config)\n","\n","model.print_trainable_parameters()"]},{"cell_type":"markdown","metadata":{},"source":["![](assets/lora-4.png)"]},{"cell_type":"code","execution_count":9,"metadata":{"execution":{"iopub.execute_input":"2023-10-05T16:08:45.751607Z","iopub.status.busy":"2023-10-05T16:08:45.750980Z","iopub.status.idle":"2023-10-05T16:08:45.755790Z","shell.execute_reply":"2023-10-05T16:08:45.754945Z","shell.execute_reply.started":"2023-10-05T16:08:45.751574Z"},"id":"QYNq0WmSKQ0Q","trusted":true},"outputs":[],"source":["# print(model)"]},{"cell_type":"code","execution_count":10,"metadata":{"execution":{"iopub.execute_input":"2023-10-05T16:08:45.760071Z","iopub.status.busy":"2023-10-05T16:08:45.759211Z","iopub.status.idle":"2023-10-05T16:08:45.768975Z","shell.execute_reply":"2023-10-05T16:08:45.768104Z","shell.execute_reply.started":"2023-10-05T16:08:45.759984Z"},"id":"mnbKMOIO9pWr","trusted":true},"outputs":[],"source":["def tokenize(sample):\n","    tokenized_text =  tokenizer(sample[\"text\"], padding=True, truncation=True, max_length=512)\n","    return tokenized_text"]},{"cell_type":"code","execution_count":12,"metadata":{"execution":{"iopub.execute_input":"2023-10-05T16:08:45.784548Z","iopub.status.busy":"2023-10-05T16:08:45.783733Z","iopub.status.idle":"2023-10-05T16:08:47.790140Z","shell.execute_reply":"2023-10-05T16:08:47.789080Z","shell.execute_reply.started":"2023-10-05T16:08:45.784516Z"},"trusted":true},"outputs":[],"source":["data = load_dataset(\"BI55/MedText\", \"main\", split=\"train\")\n","\n","data_df = data.to_pandas()"]},{"cell_type":"code","execution_count":13,"metadata":{"execution":{"iopub.execute_input":"2023-10-05T16:08:47.791843Z","iopub.status.busy":"2023-10-05T16:08:47.791453Z","iopub.status.idle":"2023-10-05T16:08:47.811861Z","shell.execute_reply":"2023-10-05T16:08:47.811336Z","shell.execute_reply.started":"2023-10-05T16:08:47.791790Z"},"trusted":true},"outputs":[],"source":["data_df[\"text\"] = data_df[[\"Prompt\", \"Completion\"]].apply(lambda x: \"Prompt: \" + x[\"Prompt\"] + \" Completion: \" + x[\"Completion\"], axis=1)"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":118,"referenced_widgets":["48a0fd6cca8343e19656719f37734014","7b402d575bd146a8b5ee8e5d58edcfed","3b39dc47d502486e8746f058664a14b7","14842fc8ca2a4b8a83e97a1aa1c2f2b3","7996196520eb41618263a6e18685b748","3221822acb5441509e57e96e57519adb","d8844e3fc47d45e2a16c44589ad6e1e6","e81c41beb7c94e7b8bb266e20e76ea05","fa0f595e81c74852b00fff8a6aad9524","42b5364769664372b81e6b002a342926","6370a57eda4446cfa96fc36a85e533f0"]},"execution":{"iopub.execute_input":"2023-10-05T16:08:47.813797Z","iopub.status.busy":"2023-10-05T16:08:47.813047Z","iopub.status.idle":"2023-10-05T16:08:48.446310Z","shell.execute_reply":"2023-10-05T16:08:48.445389Z","shell.execute_reply.started":"2023-10-05T16:08:47.813765Z"},"id":"fjszkbOx9YnY","outputId":"ba596873-7518-4109-92ff-f6bba3c27473","trusted":true},"outputs":[],"source":["data = Dataset.from_pandas(data_df)\n","\n","tokenized_data = data.map(tokenize, batched=True, desc=\"Tokenizing data\", remove_columns=data.column_names)\n","\n","tokenized_data"]},{"cell_type":"code","execution_count":15,"metadata":{"execution":{"iopub.execute_input":"2023-10-05T16:08:48.449569Z","iopub.status.busy":"2023-10-05T16:08:48.449313Z","iopub.status.idle":"2023-10-05T16:08:48.456613Z","shell.execute_reply":"2023-10-05T16:08:48.455977Z","shell.execute_reply.started":"2023-10-05T16:08:48.449546Z"},"id":"5ZVmWzSn-BO2","trusted":true},"outputs":[],"source":["training_arguments = TrainingArguments(\n","        output_dir=\"phi-1_5-finetuned-med-text\",\n","        per_device_train_batch_size=4,\n","        gradient_accumulation_steps=1,\n","        learning_rate=2e-4,\n","        lr_scheduler_type=\"cosine\",\n","        save_strategy=\"epoch\",\n","        logging_steps=100,\n","        max_steps=1000,\n","        num_train_epochs=1\n","    )"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":444},"execution":{"iopub.execute_input":"2023-10-05T16:08:48.458863Z","iopub.status.busy":"2023-10-05T16:08:48.458159Z","iopub.status.idle":"2023-10-05T16:11:02.764033Z","shell.execute_reply":"2023-10-05T16:11:02.763200Z","shell.execute_reply.started":"2023-10-05T16:08:48.458832Z"},"id":"hzggVLwo24vi","outputId":"3c8ac04b-3cde-442d-c535-2ca2e6ad6e6a","trusted":true},"outputs":[],"source":["trainer = Trainer(\n","    model=model,\n","    train_dataset=tokenized_data,\n","    args=training_arguments,\n","    data_collator=DataCollatorForLanguageModeling(tokenizer, mlm=False)\n",")\n","trainer.train()\n","\n","# trainer.push_to_hub()"]},{"cell_type":"markdown","metadata":{},"source":["## Saving"]},{"cell_type":"code","execution_count":17,"metadata":{"trusted":true},"outputs":[],"source":["model.save_pretrained(\"phi-1_5-finetuned-med-text\")"]},{"cell_type":"code","execution_count":18,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":1000,"referenced_widgets":["8f5793543b284594929ea4318e0916af","f5523f7eb6804c898135a88c33404048","8d3e81fdeb2d44c0aa5ae05f945e7f8b","c21bcf536125467d9d6bee9d69a78336","7237db4754e240baa192544c53e9613b","3e82836d3d0a40f88904122485f1e5c0","4399c4e2f3874f929047f64f35e4c306","c7e7bf1fb38f44ee9276a60ab3ead701","fd2f19ba88334f30aefc026123e113f1","f04096a8022f447ab540ff79762cbc0a","7f799a858ea84ce78b5969548fc20ccc","932f3a2286464186888c21d5965d5c28","d0b5a29ac76f4013b3c63dda6c633f18","f8c0574979544959a55152397047e956","62cda14cc0b248dcb8c867295abf1a9e","903c5a786ade4ca492c638b6c74059c2","091040823d514b53b9756a8ec98c983b","740f89bf1ac3442ea9648f9414c3789d","f5194d5ac270461c8bd019a83e33cf38","b7755e6dfca840da9e6feeec17fef720","6459ec5dc2fb498d993ae98a7bc1144f","d1ed2dea698f419780c1220e5b7b099c"]},"execution":{"iopub.execute_input":"2023-10-05T16:11:02.855190Z","iopub.status.busy":"2023-10-05T16:11:02.853182Z","iopub.status.idle":"2023-10-05T16:11:29.082578Z","shell.execute_reply":"2023-10-05T16:11:29.081380Z","shell.execute_reply.started":"2023-10-05T16:11:02.855158Z"},"id":"gztQI9_vH06k","outputId":"fc4fe676-8d36-453e-c1c8-24281117c5c1","trusted":true},"outputs":[],"source":["model = AutoModelForCausalLM.from_pretrained(\"microsoft/phi-1_5\", trust_remote_code=True, torch_dtype=torch.float32)\n","\n","peft_model = PeftModel.from_pretrained(model, \"phi-1_5-finetuned-med-text\", from_transformers=True)\n","\n","model = peft_model.merge_and_unload()\n","\n","# model"]},{"cell_type":"code","execution_count":19,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":101,"referenced_widgets":["21345dfb0bcd4273bdc3d1b1d94e8e2f","799f7f32262f474a9fca7151c807bbdb","c0f0114c6cf4409e8990d1328ba55a43","5154a4c1596f46568243002f0b429446","9e6b105d6c8d46a791f5eab83da7bc18","b49fe46213a044b097874f5b983b9d9e","187a8b28ef5f47519a22acb36430bf95","daf06ffe42ad4b018d8523684af50da1","bacdaaf282df4ba8ba77940a7e10e9c7","7415d3828c6d4a3fa89ef3f757ea7ad8","51614ca05f294a459183b248ca90516b"]},"execution":{"iopub.execute_input":"2023-10-05T16:11:29.085158Z","iopub.status.busy":"2023-10-05T16:11:29.083840Z","iopub.status.idle":"2023-10-05T16:11:54.426258Z","shell.execute_reply":"2023-10-05T16:11:54.424992Z","shell.execute_reply.started":"2023-10-05T16:11:29.085125Z"},"id":"_RD3fKuGI5pY","outputId":"f7c05768-0335-4d6f-a4bf-ffa26743c2a5","trusted":true},"outputs":[],"source":["model.save_pretrained(\"phi-1_5-finetuned-med-text\")\n","\n","# model.push_to_hub(\"llm-exp/phi-1_5-finetuned-med-text\")"]},{"cell_type":"markdown","metadata":{},"source":["## The overall flow\n","\n","1. load the base model\n","\n","2. train the base model\n","\n","3. save the LoRA adapter\n","\n","4. reload the base model at full precision\n","\n","5. merge the LoRA weights with the base model\n","\n","6. save\n"]},{"cell_type":"markdown","metadata":{"id":"xkYdH7rOJI7S"},"source":["# Inference"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":1000,"referenced_widgets":["642b14b76e6649f78a321f757e8ac93d","c00f66ef19ca4228826121a35e678f4a","6071fc5049724503ad1de25bbed27557","64f2d67fec1046038d78be994a770b33","7780ad1006244c3cb41bacacf2424522","d5d57988a2934bdcb5e884ec5fc1bfe3","5208abbacc0744e4b5fa27932cb8b30f","7c62959f0a074c4ba9bd8589a8f05b87","ec49590e8b924b94abb26fa156c9af52","adfb6748d18040fc8d25aa33523b9de0","b99353d154414d4aa49633b1e56490fe"]},"execution":{"iopub.execute_input":"2023-10-05T16:11:54.428265Z","iopub.status.busy":"2023-10-05T16:11:54.427898Z"},"id":"zZ5SXmwX3_w9","outputId":"1dce9756-3819-42ba-effa-0b0a35b68e23","trusted":true},"outputs":[],"source":["import torch\n","from transformers import AutoModelForCausalLM, AutoTokenizer\n","\n","model = AutoModelForCausalLM.from_pretrained(\"phi-1_5-finetuned-med-text\", trust_remote_code=True, torch_dtype=torch.float32)\n","\n","tokenizer = AutoTokenizer.from_pretrained(\"microsoft/phi-1_5\", trust_remote_code=True)\n","\n","inputs = tokenizer('I am having a headache with but no fever - what could be the cause', return_tensors=\"pt\", return_attention_mask=False)\n","\n","outputs = model.generate(**inputs, max_length=512)\n","\n","text = tokenizer.batch_decode(outputs)[0]\n","\n","print(text)\n"]}],"metadata":{"accelerator":"GPU","colab":{"gpuType":"T4","provenance":[]},"kernelspec":{"display_name":"Python 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