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README.md

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+---
+library_name: peft
+base_model: unsloth/tinyllama-bnb-4bit
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.11.1

adapter_config.json

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+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "unsloth/tinyllama-bnb-4bit",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_dropout": 0,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 16,
+  "rank_pattern": {},
+  "revision": "unsloth",
+  "target_modules": [
+    "gate_proj",
+    "k_proj",
+    "up_proj",
+    "o_proj",
+    "q_proj",
+    "v_proj",
+    "down_proj"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}

doc_chat_unsloth.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": "code",
+      "source": [
+        "!pip install datasets"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "c-WoJQeGyPlG",
+        "outputId": "9ff1fe05-13fc-4046-c45e-f7396b1f2250"
+      },
+      "execution_count": 2,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Collecting datasets\n",
+            "  Downloading datasets-2.19.1-py3-none-any.whl (542 kB)\n",
+            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m542.0/542.0 kB\u001b[0m \u001b[31m10.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hRequirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from datasets) (3.14.0)\n",
+            "Requirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.10/dist-packages (from datasets) (1.25.2)\n",
+            "Requirement already satisfied: pyarrow>=12.0.0 in /usr/local/lib/python3.10/dist-packages (from datasets) (14.0.2)\n",
+            "Requirement already satisfied: pyarrow-hotfix in /usr/local/lib/python3.10/dist-packages (from datasets) (0.6)\n",
+            "Collecting dill<0.3.9,>=0.3.0 (from datasets)\n",
+            "  Downloading dill-0.3.8-py3-none-any.whl (116 kB)\n",
+            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m116.3/116.3 kB\u001b[0m \u001b[31m17.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hRequirement already satisfied: pandas in /usr/local/lib/python3.10/dist-packages (from datasets) (2.0.3)\n",
+            "Requirement already satisfied: requests>=2.19.0 in /usr/local/lib/python3.10/dist-packages (from datasets) (2.31.0)\n",
+            "Requirement already satisfied: tqdm>=4.62.1 in /usr/local/lib/python3.10/dist-packages (from datasets) (4.66.4)\n",
+            "Collecting xxhash (from datasets)\n",
+            "  Downloading xxhash-3.4.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (194 kB)\n",
+            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m194.1/194.1 kB\u001b[0m \u001b[31m29.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hCollecting multiprocess (from datasets)\n",
+            "  Downloading multiprocess-0.70.16-py310-none-any.whl (134 kB)\n",
+            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m134.8/134.8 kB\u001b[0m \u001b[31m21.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hRequirement already satisfied: fsspec[http]<=2024.3.1,>=2023.1.0 in /usr/local/lib/python3.10/dist-packages (from datasets) (2023.6.0)\n",
+            "Requirement already satisfied: aiohttp in /usr/local/lib/python3.10/dist-packages (from datasets) (3.9.5)\n",
+            "Requirement already satisfied: huggingface-hub>=0.21.2 in /usr/local/lib/python3.10/dist-packages (from datasets) (0.23.1)\n",
+            "Requirement already satisfied: packaging in /usr/local/lib/python3.10/dist-packages (from datasets) (24.0)\n",
+            "Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.10/dist-packages (from datasets) (6.0.1)\n",
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+            "Requirement already satisfied: attrs>=17.3.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets) (23.2.0)\n",
+            "Requirement already satisfied: frozenlist>=1.1.1 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets) (1.4.1)\n",
+            "Requirement already satisfied: multidict<7.0,>=4.5 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets) (6.0.5)\n",
+            "Requirement already satisfied: yarl<2.0,>=1.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets) (1.9.4)\n",
+            "Requirement already satisfied: async-timeout<5.0,>=4.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets) (4.0.3)\n",
+            "Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub>=0.21.2->datasets) (4.11.0)\n",
+            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests>=2.19.0->datasets) (3.3.2)\n",
+            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests>=2.19.0->datasets) (3.7)\n",
+            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests>=2.19.0->datasets) (2.0.7)\n",
+            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests>=2.19.0->datasets) (2024.2.2)\n",
+            "Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.10/dist-packages (from pandas->datasets) (2.8.2)\n",
+            "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.10/dist-packages (from pandas->datasets) (2023.4)\n",
+            "Requirement already satisfied: tzdata>=2022.1 in /usr/local/lib/python3.10/dist-packages (from pandas->datasets) (2024.1)\n",
+            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil>=2.8.2->pandas->datasets) (1.16.0)\n",
+            "Installing collected packages: xxhash, dill, multiprocess, datasets\n",
+            "Successfully installed datasets-2.19.1 dill-0.3.8 multiprocess-0.70.16 xxhash-3.4.1\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "!pip install \"unsloth[colab-new] @ git+https://github.com/unslothai/unsloth.git\"\n",
+        "!pip install --no-deps xformers trl peft accelerate bitsandbytes"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "bNRY4EekyVv0",
+        "outputId": "337e20ec-32fb-473a-ce75-1b4602b3e05a"
+      },
+      "execution_count": 3,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Collecting unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git\n",
+            "  Cloning https://github.com/unslothai/unsloth.git to /tmp/pip-install-yz9b4cgg/unsloth_b0255de764894292a5ad70b60132ae17\n",
+            "  Running command git clone --filter=blob:none --quiet https://github.com/unslothai/unsloth.git /tmp/pip-install-yz9b4cgg/unsloth_b0255de764894292a5ad70b60132ae17\n",
+            "  Resolved https://github.com/unslothai/unsloth.git to commit cd1b44878686972d1de60e905215825da330f1e1\n",
+            "  Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n",
+            "  Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n",
+            "  Installing backend dependencies ... \u001b[?25l\u001b[?25hdone\n",
+            "  Preparing metadata (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
+            "Collecting tyro (from unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git)\n",
+            "  Downloading tyro-0.8.4-py3-none-any.whl (102 kB)\n",
+            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m102.4/102.4 kB\u001b[0m \u001b[31m3.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hRequirement already satisfied: transformers>=4.38.2 in /usr/local/lib/python3.10/dist-packages (from unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (4.41.1)\n",
+            "Requirement already satisfied: datasets>=2.16.0 in /usr/local/lib/python3.10/dist-packages (from unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (2.19.1)\n",
+            "Requirement already satisfied: sentencepiece in /usr/local/lib/python3.10/dist-packages (from unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (0.1.99)\n",
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+            "Requirement already satisfied: numpy in /usr/local/lib/python3.10/dist-packages (from unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (1.25.2)\n",
+            "Requirement already satisfied: protobuf<4.0.0 in /usr/local/lib/python3.10/dist-packages (from unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (3.20.3)\n",
+            "Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from datasets>=2.16.0->unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (3.14.0)\n",
+            "Requirement already satisfied: pyarrow>=12.0.0 in /usr/local/lib/python3.10/dist-packages (from datasets>=2.16.0->unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (14.0.2)\n",
+            "Requirement already satisfied: pyarrow-hotfix in /usr/local/lib/python3.10/dist-packages (from datasets>=2.16.0->unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (0.6)\n",
+            "Requirement already satisfied: dill<0.3.9,>=0.3.0 in /usr/local/lib/python3.10/dist-packages (from datasets>=2.16.0->unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (0.3.8)\n",
+            "Requirement already satisfied: pandas in /usr/local/lib/python3.10/dist-packages (from datasets>=2.16.0->unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (2.0.3)\n",
+            "Requirement already satisfied: requests>=2.19.0 in /usr/local/lib/python3.10/dist-packages (from datasets>=2.16.0->unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (2.31.0)\n",
+            "Requirement already satisfied: xxhash in /usr/local/lib/python3.10/dist-packages (from datasets>=2.16.0->unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (3.4.1)\n",
+            "Requirement already satisfied: multiprocess in /usr/local/lib/python3.10/dist-packages (from datasets>=2.16.0->unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (0.70.16)\n",
+            "Requirement already satisfied: fsspec[http]<=2024.3.1,>=2023.1.0 in /usr/local/lib/python3.10/dist-packages (from datasets>=2.16.0->unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (2023.6.0)\n",
+            "Requirement already satisfied: aiohttp in /usr/local/lib/python3.10/dist-packages (from datasets>=2.16.0->unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (3.9.5)\n",
+            "Requirement already satisfied: huggingface-hub>=0.21.2 in /usr/local/lib/python3.10/dist-packages (from datasets>=2.16.0->unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (0.23.1)\n",
+            "Requirement already satisfied: packaging in /usr/local/lib/python3.10/dist-packages (from datasets>=2.16.0->unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (24.0)\n",
+            "Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.10/dist-packages (from datasets>=2.16.0->unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (6.0.1)\n",
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+            "Requirement already satisfied: tokenizers<0.20,>=0.19 in /usr/local/lib/python3.10/dist-packages (from transformers>=4.38.2->unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (0.19.1)\n",
+            "Requirement already satisfied: safetensors>=0.4.1 in /usr/local/lib/python3.10/dist-packages (from transformers>=4.38.2->unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (0.4.3)\n",
+            "Requirement already satisfied: docstring-parser>=0.14.1 in /usr/local/lib/python3.10/dist-packages (from tyro->unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (0.16)\n",
+            "Requirement already satisfied: typing-extensions>=4.7.0 in /usr/local/lib/python3.10/dist-packages (from tyro->unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (4.11.0)\n",
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+            "Collecting shtab>=1.5.6 (from tyro->unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git)\n",
+            "  Downloading shtab-1.7.1-py3-none-any.whl (14 kB)\n",
+            "Requirement already satisfied: aiosignal>=1.1.2 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets>=2.16.0->unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (1.3.1)\n",
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+            "Requirement already satisfied: async-timeout<5.0,>=4.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets>=2.16.0->unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (4.0.3)\n",
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+            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests>=2.19.0->datasets>=2.16.0->unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (3.7)\n",
+            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests>=2.19.0->datasets>=2.16.0->unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (2.0.7)\n",
+            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests>=2.19.0->datasets>=2.16.0->unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (2024.2.2)\n",
+            "Requirement already satisfied: markdown-it-py>=2.2.0 in /usr/local/lib/python3.10/dist-packages (from rich>=11.1.0->tyro->unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (3.0.0)\n",
+            "Requirement already satisfied: pygments<3.0.0,>=2.13.0 in /usr/local/lib/python3.10/dist-packages (from rich>=11.1.0->tyro->unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (2.16.1)\n",
+            "Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.10/dist-packages (from pandas->datasets>=2.16.0->unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (2.8.2)\n",
+            "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.10/dist-packages (from pandas->datasets>=2.16.0->unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (2023.4)\n",
+            "Requirement already satisfied: tzdata>=2022.1 in /usr/local/lib/python3.10/dist-packages (from pandas->datasets>=2.16.0->unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (2024.1)\n",
+            "Requirement already satisfied: mdurl~=0.1 in /usr/local/lib/python3.10/dist-packages (from markdown-it-py>=2.2.0->rich>=11.1.0->tyro->unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (0.1.2)\n",
+            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil>=2.8.2->pandas->datasets>=2.16.0->unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (1.16.0)\n",
+            "Building wheels for collected packages: unsloth\n",
+            "  Building wheel for unsloth (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
+            "  Created wheel for unsloth: filename=unsloth-2024.5-py3-none-any.whl size=109128 sha256=d07640c7a49efaa3dcfbf645a27e7b8a03b25d97d757255165955b28d50c7c65\n",
+            "  Stored in directory: /tmp/pip-ephem-wheel-cache-74zy8n65/wheels/ed/d4/e9/76fb290ee3df0a5fc21ce5c2c788e29e9607a2353d8342fd0d\n",
+            "Successfully built unsloth\n",
+            "Installing collected packages: unsloth, shtab, tyro\n",
+            "Successfully installed shtab-1.7.1 tyro-0.8.4 unsloth-2024.5\n",
+            "Collecting xformers\n",
+            "  Downloading xformers-0.0.26.post1-cp310-cp310-manylinux2014_x86_64.whl (222.7 MB)\n",
+            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m222.7/222.7 MB\u001b[0m \u001b[31m5.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hCollecting trl\n",
+            "  Downloading trl-0.8.6-py3-none-any.whl (245 kB)\n",
+            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m245.2/245.2 kB\u001b[0m \u001b[31m36.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hCollecting peft\n",
+            "  Downloading peft-0.11.1-py3-none-any.whl (251 kB)\n",
+            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m251.6/251.6 kB\u001b[0m \u001b[31m38.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hCollecting accelerate\n",
+            "  Downloading accelerate-0.30.1-py3-none-any.whl (302 kB)\n",
+            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m302.6/302.6 kB\u001b[0m \u001b[31m43.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hCollecting bitsandbytes\n",
+            "  Downloading bitsandbytes-0.43.1-py3-none-manylinux_2_24_x86_64.whl (119.8 MB)\n",
+            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m119.8/119.8 MB\u001b[0m \u001b[31m8.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hInstalling collected packages: bitsandbytes, xformers, trl, peft, accelerate\n",
+            "Successfully installed accelerate-0.30.1 bitsandbytes-0.43.1 peft-0.11.1 trl-0.8.6 xformers-0.0.26.post1\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "from datasets import load_dataset,Dataset\n",
+        "import torch\n",
+        "from transformers import AutoModelForCausalLM, AutoTokenizer, BitsAndBytesConfig\n",
+        "from peft import prepare_model_for_kbit_training, LoraConfig, TaskType, get_peft_model\n",
+        "from transformers import TrainingArguments\n",
+        "from trl import SFTTrainer\n",
+        "from peft import AutoPeftModelForCausalLM, PeftModel\n",
+        "from transformers import AutoModelForCausalLM\n",
+        "import os\n",
+        "from transformers import GenerationConfig\n",
+        "from time import perf_counter\n",
+        "from unsloth import FastLanguageModel\n",
+        "from unsloth import is_bfloat16_supported"
+      ],
+      "metadata": {
+        "id": "-ixC4T7wztdx"
+      },
+      "execution_count": 38,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "model_id = \"unsloth/tinyllama-bnb-4bit\"\n",
+        "data_id = 'Malikeh1375/medical-question-answering-datasets'\n",
+        "output_model = 'doctor_chat_LLM_150_unsloth'\n",
+        "\n",
+        "def prepare_train_data(data_id):\n",
+        "    data = load_dataset(data_id, 'all-processed',split=\"train\")\n",
+        "    data_df = data.to_pandas()\n",
+        "    data_df[\"text\"] = data_df[['instruction','input','output']].apply(lambda x: \"<|Instruction|>\\n\" + x[\"instruction\"]  +\"</s>\\n<|Input|>\\n\" + x[\"input\"] + \"</s>\\n<|Output|>\\n\"+x['output']+\"</s>\", axis=1)\n",
+        "    data = Dataset.from_pandas(data_df)\n",
+        "    return data\n",
+        "\n",
+        "train_data = prepare_train_data(data_id).shuffle(seed=42).select(range(500))\n",
+        "\n",
+        "print(train_data[0]['text'])"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "ZHptL3OqEhdi",
+        "outputId": "ccd438ee-f4d1-46e4-dda7-2cae7847aa69"
+      },
+      "execution_count": 50,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "<|Instruction|>\n",
+            "If you are a doctor, please answer the medical questions based on the patient's description.</s>\n",
+            "<|Input|>\n",
+            "Hi, may I answer your health queries right now ?  Please type your query here...SIR MY PROBLEM IS   SOME TIME AFTER URINATION ,I FELT LIKE SOME THING IS COMING FROM MY PENIS & A CAN SEE THIS IS OILY THICKY SOME DROPE IS COMING & IT IS VERY OILY & LUBRICANT TYPE   WHAT IS THIS   I M VERY WORRIED</s>\n",
+            "<|Output|>\n",
+            "hi, if you are sexually active then there is a high chance that you may have had a sexually transmitted disease. you need to see a doctor and the fluid would be tested for different types of bacteria, fungi and viruses. you may also need some antibiotics to ensure that you are treated properly. if you are not sexually active it is better also to have the fluid checked for its composition so that we will be able to provide proper management and treatment for your case. hope i have answered your query. let me know if i can assist you further.</s>\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "print(train_data[1]['text'])"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "57puJnWr40rp",
+        "outputId": "13d46aa8-cf0d-4c67-b0b4-fbd01fb7d4be"
+      },
+      "execution_count": 51,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "<|Instruction|>\n",
+            "If you are a doctor, please answer the medical questions based on the patient's description.</s>\n",
+            "<|Input|>\n",
+            "Hi,i have undergone several tests like uv scan,trans vaginal scan and blood tests including hormonal tests and thyroid tests etc. but everything seems normal.we r trying for pregnancy for last one and half year and he too had normal sperm count but we couldn t succeed.i m using trufol,benforce-m and a to z gold multiitamin tablet from before 1 month.i used to get regular periods.in december i have taken premoult to delay my period for some reason and after stopping it i have my period after 3 days ie. dec 25th and in january i have period on 20th but know i missed my period till know and pregnancy test is negative.is their any problem with medicines i mentioned above for delayed period.</s>\n",
+            "<|Output|>\n",
+            "hi, thanks for your question. i don't think the medicine you are on, or have had could have caused this period problem. you have not provided the details of your test results & from the medicine you are taking i have guessed that you may have an ovulation problem (since you are on metformin, are unable to conceive & have delayed periods). so, my suggestion for you is to register yourself at a good fertility clinic with your partner & get yourself fully evaluated. once a cause is found you may be offered a specific treatment which may be ovulation induction in your case. wish you best of luck</s>\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "train_data"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "F9xwbYPD107L",
+        "outputId": "a17be6ac-de80-4013-f17d-f8d64794f335"
+      },
+      "execution_count": 52,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "Dataset({\n",
+              "    features: ['instruction', 'input', 'output', '__index_level_0__', 'text'],\n",
+              "    num_rows: 500\n",
+              "})"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 52
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "model, tokenizer = FastLanguageModel.from_pretrained(\n",
+        "    model_name = \"unsloth/tinyllama-bnb-4bit\", # \"unsloth/tinyllama\" for 16bit loading\n",
+        "    max_seq_length = 1500,\n",
+        "    dtype = None,\n",
+        "    load_in_4bit = True,\n",
+        "    # token = \"hf_...\", # use one if using gated models like meta-llama/Llama-2-7b-hf\n",
+        ")\n",
+        "\n",
+        "print(model)"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 499
+        },
+        "id": "Ic5lF0DNyLji",
+        "outputId": "8c70c2f6-af0d-4b99-c60f-a7dc81df06d4"
+      },
+      "execution_count": 54,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "==((====))==  Unsloth: Fast Llama patching release 2024.5\n",
+            "   \\\\   /|    GPU: Tesla T4. Max memory: 14.748 GB. Platform = Linux.\n",
+            "O^O/ \\_/ \\    Pytorch: 2.3.0+cu121. CUDA = 7.5. CUDA Toolkit = 12.1.\n",
+            "\\        /    Bfloat16 = FALSE. Xformers = 0.0.26.post1. FA = False.\n",
+            " \"-____-\"     Free Apache license: http://github.com/unslothai/unsloth\n"
+          ]
+        },
+        {
+          "output_type": "error",
+          "ename": "ValueError",
+          "evalue": "Some modules are dispatched on the CPU or the disk. Make sure you have enough GPU RAM to fit the quantized model. If you want to dispatch the model on the CPU or the disk while keeping these modules in 32-bit, you need to set `load_in_8bit_fp32_cpu_offload=True` and pass a custom `device_map` to `from_pretrained`. Check https://huggingface.co/docs/transformers/main/en/main_classes/quantization#offload-between-cpu-and-gpu for more details. ",
+          "traceback": [
+            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+            "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
+            "\u001b[0;32m<ipython-input-54-43ef74bf5388>\u001b[0m in \u001b[0;36m<cell line: 1>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m model, tokenizer = FastLanguageModel.from_pretrained(\n\u001b[0m\u001b[1;32m      2\u001b[0m     \u001b[0mmodel_name\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m\"unsloth/tinyllama-bnb-4bit\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;31m# \"unsloth/tinyllama\" for 16bit loading\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m     \u001b[0mmax_seq_length\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m1000\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m     \u001b[0mdtype\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m     \u001b[0mload_in_4bit\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/unsloth/models/loader.py\u001b[0m in \u001b[0;36mfrom_pretrained\u001b[0;34m(model_name, max_seq_length, dtype, load_in_4bit, token, device_map, rope_scaling, fix_tokenizer, trust_remote_code, use_gradient_checkpointing, resize_model_vocab, *args, **kwargs)\u001b[0m\n\u001b[1;32m    140\u001b[0m         \u001b[0;32mpass\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    141\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 142\u001b[0;31m         model, tokenizer = dispatch_model.from_pretrained(\n\u001b[0m\u001b[1;32m    143\u001b[0m             \u001b[0mmodel_name\u001b[0m     \u001b[0;34m=\u001b[0m \u001b[0mmodel_name\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    144\u001b[0m             \u001b[0mmax_seq_length\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmax_seq_length\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/unsloth/models/llama.py\u001b[0m in \u001b[0;36mfrom_pretrained\u001b[0;34m(model_name, max_seq_length, dtype, load_in_4bit, token, device_map, rope_scaling, fix_tokenizer, model_patcher, tokenizer_name, trust_remote_code, **kwargs)\u001b[0m\n\u001b[1;32m   1133\u001b[0m                 )\n\u001b[1;32m   1134\u001b[0m             \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1135\u001b[0;31m                 \u001b[0;32mraise\u001b[0m \u001b[0merror\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1136\u001b[0m             \u001b[0;32mpass\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1137\u001b[0m         \u001b[0;32mpass\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/unsloth/models/llama.py\u001b[0m in \u001b[0;36mfrom_pretrained\u001b[0;34m(model_name, max_seq_length, dtype, load_in_4bit, token, device_map, rope_scaling, fix_tokenizer, model_patcher, tokenizer_name, trust_remote_code, **kwargs)\u001b[0m\n\u001b[1;32m   1104\u001b[0m         \u001b[0mmax_position_embeddings\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmax\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmax_seq_length\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmodel_max_seq_length\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1105\u001b[0m         \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1106\u001b[0;31m             model = AutoModelForCausalLM.from_pretrained(\n\u001b[0m\u001b[1;32m   1107\u001b[0m                 \u001b[0mmodel_name\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1108\u001b[0m                 \u001b[0mdevice_map\u001b[0m              \u001b[0;34m=\u001b[0m \u001b[0mdevice_map\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/transformers/models/auto/auto_factory.py\u001b[0m in \u001b[0;36mfrom_pretrained\u001b[0;34m(cls, pretrained_model_name_or_path, *model_args, **kwargs)\u001b[0m\n\u001b[1;32m    561\u001b[0m         \u001b[0;32melif\u001b[0m \u001b[0mtype\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mconfig\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mcls\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_model_mapping\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mkeys\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    562\u001b[0m             \u001b[0mmodel_class\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_get_model_class\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mconfig\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcls\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_model_mapping\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 563\u001b[0;31m             return model_class.from_pretrained(\n\u001b[0m\u001b[1;32m    564\u001b[0m                 \u001b[0mpretrained_model_name_or_path\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0mmodel_args\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mconfig\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mconfig\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mhub_kwargs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    565\u001b[0m             )\n",
+            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/transformers/modeling_utils.py\u001b[0m in \u001b[0;36mfrom_pretrained\u001b[0;34m(cls, pretrained_model_name_or_path, config, cache_dir, ignore_mismatched_sizes, force_download, local_files_only, token, revision, use_safetensors, *model_args, **kwargs)\u001b[0m\n\u001b[1;32m   3701\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3702\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mhf_quantizer\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3703\u001b[0;31m                 \u001b[0mhf_quantizer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalidate_environment\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdevice_map\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdevice_map\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   3704\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3705\u001b[0m         \u001b[0;32melif\u001b[0m \u001b[0mdevice_map\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/transformers/quantizers/quantizer_bnb_4bit.py\u001b[0m in \u001b[0;36mvalidate_environment\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m     83\u001b[0m             }\n\u001b[1;32m     84\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0;34m\"cpu\"\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mdevice_map_without_lm_head\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalues\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0;34m\"disk\"\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mdevice_map_without_lm_head\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalues\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 85\u001b[0;31m                 raise ValueError(\n\u001b[0m\u001b[1;32m     86\u001b[0m                     \u001b[0;34m\"Some modules are dispatched on the CPU or the disk. Make sure you have enough GPU RAM to fit the \"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     87\u001b[0m                     \u001b[0;34m\"quantized model. If you want to dispatch the model on the CPU or the disk while keeping these modules \"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+            "\u001b[0;31mValueError\u001b[0m: Some modules are dispatched on the CPU or the disk. Make sure you have enough GPU RAM to fit the quantized model. If you want to dispatch the model on the CPU or the disk while keeping these modules in 32-bit, you need to set `load_in_8bit_fp32_cpu_offload=True` and pass a custom `device_map` to `from_pretrained`. Check https://huggingface.co/docs/transformers/main/en/main_classes/quantization#offload-between-cpu-and-gpu for more details. "
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "model = FastLanguageModel.get_peft_model(\n",
+        "    model,\n",
+        "    r = 16, # Choose any number > 0 ! Suggested 8, 16, 32, 64, 128\n",
+        "    target_modules = [\"q_proj\", \"k_proj\", \"v_proj\", \"o_proj\",\n",
+        "                      \"gate_proj\", \"up_proj\", \"down_proj\",],\n",
+        "    lora_alpha = 32,\n",
+        "    lora_dropout = 0, # Currently only supports dropout = 0\n",
+        "    bias = \"none\",    # Currently only supports bias = \"none\"\n",
+        "    use_gradient_checkpointing = True, # @@@ IF YOU GET OUT OF MEMORY - set to True @@@\n",
+        "    random_state = 42,\n",
+        "    use_rslora = False,  # We support rank stabilized LoRA\n",
+        "    loftq_config = None, # And LoftQ\n",
+        ")"
+      ],
+      "metadata": {
+        "id": "-EGbwycpzb4j"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "trainer = SFTTrainer(\n",
+        "    model = model,\n",
+        "    tokenizer = tokenizer,\n",
+        "    train_dataset = train_data,\n",
+        "    dataset_text_field = \"text\",\n",
+        "    max_seq_length = 1500,\n",
+        "    packing = True, # Packs short sequences together to save time!\n",
+        "    args = TrainingArguments(\n",
+        "        per_device_train_batch_size = 8,\n",
+        "        gradient_accumulation_steps = 4,\n",
+        "        warmup_ratio = 0.1,\n",
+        "        num_train_epochs = 10,\n",
+        "        max_steps=200,\n",
+        "        learning_rate = 2e-5,\n",
+        "        fp16 = not is_bfloat16_supported(),\n",
+        "        bf16 = is_bfloat16_supported(),\n",
+        "        logging_steps = 1,\n",
+        "        optim = \"adamw_8bit\",\n",
+        "        weight_decay = 0.1,\n",
+        "        lr_scheduler_type = \"linear\",\n",
+        "        output_dir = output_model,\n",
+        "    ),\n",
+        ")\n",
+        "trainer.train()"
+      ],
+      "metadata": {
+        "id": "Qy6yK4FLze4f"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "train_data[1]['text']"
+      ],
+      "metadata": {
+        "id": "wBEwT9up9DSz"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "FastLanguageModel.for_inference(model)\n",
+        "\n",
+        "def formatted_prompt(Instruction,input)-> str:\n",
+        "    return f\"<|Instruction|>\\n{Instruction}</s>\\n<|input|>\\n{input}</s>\\n<|output|>\"\n",
+        "\n",
+        "def generate_response(Instruction,user_input):\n",
+        "\n",
+        "  prompt = formatted_prompt(Instruction,user_input)\n",
+        "  print(prompt)\n",
+        "\n",
+        "  start_time = perf_counter()\n",
+        "\n",
+        "  inputs = tokenizer(prompt, return_tensors=\"pt\").to('cuda')\n",
+        "\n",
+        "  outputs = model.generate(**inputs, max_new_tokens = 150, use_cache = True)\n",
+        "  print(tokenizer.batch_decode(outputs))\n",
+        "  output_time = perf_counter() - start_time\n",
+        "  print(f\"Time taken for inference: {round(output_time,2)} seconds\")\n",
+        "\n",
+        "\n",
+        "Instruction = \"If you are a doctor, please answer the medical questions based on the patient's description.\"\n",
+        "user_input = 'I am a 20 year old boy.I am having frequent headaches what should i do?What temprory steps should i take?'\n",
+        "\n",
+        "generate_response(Instruction,user_input)"
+      ],
+      "metadata": {
+        "id": "32lR_kynzmuv"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [],
+      "metadata": {
+        "id": "9FulpdS10A_X"
+      },
+      "execution_count": null,
+      "outputs": []
+    }
+  ]
+}

special_tokens_map.json

@@ -0,0 +1,30 @@
+{
+  "bos_token": {
+    "content": "<s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "<unk>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "unk_token": {
+    "content": "<unk>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer.model

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9e556afd44213b6bd1be2b850ebbbd98f5481437a8021afaf58ee7fb1818d347
+size 499723