diff --git a/.gitignore b/.gitignore
new file mode 100644
index 0000000..8af9042
--- /dev/null
+++ b/.gitignore
@@ -0,0 +1,174 @@
+###############################################################################
+# Repo specific .gitignore
+###############################################################################
+llama.cpp/
+original_model/
+quantized_model/
+
+
+###############################################################################
+# Standard .gitignore file for Python projects
+###############################################################################
+
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+#   For a library or package, you might want to ignore these files since the code is
+#   intended to run in multiple environments; otherwise, check them in:
+# .python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# poetry
+#   Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#   https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
+#poetry.lock
+
+# pdm
+#   Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
+#pdm.lock
+#   pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
+#   in version control.
+#   https://pdm.fming.dev/latest/usage/project/#working-with-version-control
+.pdm.toml
+.pdm-python
+.pdm-build/
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+
+# PyCharm
+#  JetBrains specific template is maintained in a separate JetBrains.gitignore that can
+#  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
+#  and can be added to the global gitignore or merged into this file.  For a more nuclear
+#  option (not recommended) you can uncomment the following to ignore the entire idea folder.
+#.idea/
diff --git a/QuantizeLLMs.ipynb b/QuantizeLLMs.ipynb
index a5acf46..b7bd45f 100644
--- a/QuantizeLLMs.ipynb
+++ b/QuantizeLLMs.ipynb
@@ -3,8 +3,8 @@
     {
       "cell_type": "markdown",
       "metadata": {
-        "id": "view-in-github",
-        "colab_type": "text"
+        "colab_type": "text",
+        "id": "view-in-github"
       },
       "source": [
         "<a href=\"https://colab.research.google.com/github/mickymultani/QuantizeLLMs/blob/main/QuantizeLLMs.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
@@ -18,7 +18,7 @@
       },
       "outputs": [],
       "source": [
-        "!!git clone https://github.com/ggerganov/llama.cpp"
+        "!!git clone --branch b3978 https://github.com/ggerganov/llama.cpp.git"
       ]
     },
     {
@@ -29,188 +29,181 @@
       },
       "outputs": [],
       "source": [
-        "!cd llama.cpp && LLAMA_CUBLAS=1 make && pip install -r requirements.txt"
+        "!cd llama.cpp && GGML_CUDA=1 make && pip install -r requirements.txt"
       ]
     },
     {
       "cell_type": "code",
-      "source": [
-        "from huggingface_hub import snapshot_download"
-      ],
+      "execution_count": null,
       "metadata": {
         "id": "HF6yYzNZtd19"
       },
-      "execution_count": 3,
-      "outputs": []
+      "outputs": [],
+      "source": [
+        "from huggingface_hub import snapshot_download"
+      ]
     },
     {
       "cell_type": "code",
-      "source": [
-        "model_name = \"google/gemma-2b-it\""
-      ],
+      "execution_count": null,
       "metadata": {
         "id": "vw5v0tF_t6qX"
       },
-      "execution_count": 4,
-      "outputs": []
+      "outputs": [],
+      "source": [
+        "model_name = \"google/gemma-2b-it\""
+      ]
     },
     {
       "cell_type": "code",
-      "source": [
-        "methods = [\"q4_k_m\"]"
-      ],
+      "execution_count": null,
       "metadata": {
         "id": "aq5DxDOiubm-"
       },
-      "execution_count": 5,
-      "outputs": []
+      "outputs": [],
+      "source": [
+        "methods = [\"q4_k_m\"]"
+      ]
     },
     {
       "cell_type": "code",
-      "source": [
-        "base_model = \"./orignal_model/\""
-      ],
+      "execution_count": null,
       "metadata": {
         "id": "yR27LvA_uwYm"
       },
-      "execution_count": 6,
-      "outputs": []
+      "outputs": [],
+      "source": [
+        "base_model = \"./original_model/\""
+      ]
     },
     {
       "cell_type": "code",
-      "source": [
-        "quantized_path = \"./quantized_model/\""
-      ],
+      "execution_count": null,
       "metadata": {
         "id": "x4Ciwal7u5jx"
       },
-      "execution_count": 7,
-      "outputs": []
+      "outputs": [],
+      "source": [
+        "quantized_path = \"./quantized_model/\""
+      ]
     },
     {
       "cell_type": "code",
-      "source": [
-        "snapshot_download(repo_id=model_name, local_dir=base_model, local_dir_use_symlinks=False)"
-      ],
+      "execution_count": null,
       "metadata": {
         "id": "mUBryZ1wvSF6"
       },
-      "execution_count": null,
-      "outputs": []
+      "outputs": [],
+      "source": [
+        "snapshot_download(repo_id=model_name, local_dir=base_model, local_dir_use_symlinks=False)"
+      ]
     },
     {
       "cell_type": "code",
-      "source": [
-        "orignal_model = quantized_path+\"/fp16.gguf\""
-      ],
+      "execution_count": null,
       "metadata": {
         "id": "5oFgQ1Pgw7eD"
       },
-      "execution_count": 9,
-      "outputs": []
+      "outputs": [],
+      "source": [
+        "original_model = quantized_path+\"/fp16.gguf\""
+      ]
     },
     {
       "cell_type": "code",
-      "source": [
-        "!mkdir ./quantized_model/"
-      ],
+      "execution_count": null,
       "metadata": {
         "id": "K9ANvmOtxLEg"
       },
-      "execution_count": 10,
-      "outputs": []
+      "outputs": [],
+      "source": [
+        "!mkdir ./quantized_model/"
+      ]
     },
     {
       "cell_type": "code",
-      "source": [
-        "!python llama.cpp/convert-hf-to-gguf.py ./orignal_model/ --outtype f16 --outfile ./quantized_model/FP16.gguf"
-      ],
+      "execution_count": null,
       "metadata": {
         "id": "ue-353Tj2ZFv"
       },
-      "execution_count": null,
-      "outputs": []
+      "outputs": [],
+      "source": [
+        "!python llama.cpp/convert_hf_to_gguf.py ./original_model/ --outtype f16 --outfile ./quantized_model/FP16.gguf"
+      ]
     },
     {
       "cell_type": "code",
-      "source": [
-        "import os"
-      ],
+      "execution_count": null,
       "metadata": {
         "id": "c7XTrFZh25ww"
       },
-      "execution_count": 14,
-      "outputs": []
+      "outputs": [],
+      "source": [
+        "import os"
+      ]
     },
     {
       "cell_type": "code",
-      "source": [
-        "for m in methods:\n",
-        "  qtype = f\"{quantized_path}/{m.upper()}.gguf\"\n",
-        "  os.system(\"./llama.cpp/quantize \"+quantized_path+\"/FP16.gguf \"+qtype+\" \"+m)"
-      ],
+      "execution_count": null,
       "metadata": {
         "id": "vGU2XSuH4W4I"
       },
-      "execution_count": 15,
-      "outputs": []
+      "outputs": [],
+      "source": [
+        "for m in methods:\n",
+        "  qtype = f\"{quantized_path}/{m.upper()}.gguf\"\n",
+        "  os.system(\"./llama.cpp/llama-quantize \"+quantized_path+\"/FP16.gguf \"+qtype+\" \"+m)"
+      ]
     },
     {
       "cell_type": "code",
-      "source": [
-        "! ./llama.cpp/main -m ./quantized_model/Q4_K_M.gguf -n 90 --repeat_penalty 1.0 --color -i -r \"User: \" -f llama.cpp/prompts/chat-with-bob.txt"
-      ],
+      "execution_count": null,
       "metadata": {
         "id": "oML4taGB6I6l"
       },
-      "execution_count": null,
-      "outputs": []
+      "outputs": [],
+      "source": [
+        "! ./llama.cpp/llama-cli -m ./quantized_model/Q4_K_M.gguf -n 90 --repeat_penalty 1.0 --color -i -r \"User: \" -f llama.cpp/prompts/chat-with-bob.txt"
+      ]
     },
     {
       "cell_type": "code",
-      "source": [
-        "from huggingface_hub import HfApi, HfFolder, create_repo, upload_file"
-      ],
+      "execution_count": null,
       "metadata": {
         "id": "C3gXkTXLAetI"
       },
-      "execution_count": 18,
-      "outputs": []
+      "outputs": [],
+      "source": [
+        "from huggingface_hub import HfApi, HfFolder, create_repo, upload_file"
+      ]
     },
     {
       "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "kiMSy2PuAwG2"
+      },
+      "outputs": [],
       "source": [
         "model_path = \"./quantized_model/Q4_K_M.gguf\"\n",
         "repo_name = \"gemma-2b-it-GGUF-quantized\"\n",
         "repo_url = create_repo(repo_name, private=False)"
-      ],
-      "metadata": {
-        "id": "kiMSy2PuAwG2"
-      },
-      "execution_count": 19,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "code",
-      "source": [
-        "api = HfApi()"
-      ],
+      "execution_count": null,
       "metadata": {
         "id": "gOfEfRgbB47f"
       },
-      "execution_count": 20,
-      "outputs": []
+      "outputs": [],
+      "source": [
+        "api = HfApi()"
+      ]
     },
     {
       "cell_type": "code",
-      "source": [
-        "api.upload_file(\n",
-        "    path_or_fileobj=model_path,\n",
-        "    path_in_repo=\"Q4_K_M.gguf\",\n",
-        "    repo_id= \"yourusername/gemma-2b-it-GGUF-quantized\",\n",
-        "    repo_type=\"model\",\n",
-        ")"
-      ],
+      "execution_count": null,
       "metadata": {
         "colab": {
           "base_uri": "https://localhost:8080/",
@@ -232,59 +225,47 @@
         "id": "DVd1C5IxB_eG",
         "outputId": "e82bac0b-8ff8-4753-f451-787114ee5d94"
       },
-      "execution_count": 21,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "Q4_K_M.gguf:   0%|          | 0.00/1.63G [00:00<?, ?B/s]"
-            ],
-            "application/vnd.jupyter.widget-view+json": {
-              "version_major": 2,
-              "version_minor": 0,
-              "model_id": "142c94d6f7b54cdca12596df1892e09d"
-            }
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/plain": [
-              "CommitInfo(commit_url='https://huggingface.co/mickymultani/gemma-2b-it-GGUF-quantized/commit/92903f66bb4e303c20ff1e6262f77370172cd0ac', commit_message='Upload Q4_K_M.gguf with huggingface_hub', commit_description='', oid='92903f66bb4e303c20ff1e6262f77370172cd0ac', pr_url=None, pr_revision=None, pr_num=None)"
-            ],
-            "application/vnd.google.colaboratory.intrinsic+json": {
-              "type": "string"
-            }
-          },
-          "metadata": {},
-          "execution_count": 21
-        }
+      "outputs": [],
+      "source": [
+        "api.upload_file(\n",
+        "    path_or_fileobj=model_path,\n",
+        "    path_in_repo=\"Q4_K_M.gguf\",\n",
+        "    repo_id= \"<yourusername>/gemma-2b-it-GGUF-quantized\",\n",
+        "    repo_type=\"model\",\n",
+        ")"
       ]
     }
   ],
   "metadata": {
     "accelerator": "GPU",
     "colab": {
-      "gpuType": "T4",
-      "provenance": [],
       "authorship_tag": "ABX9TyM0nMUdZgPDDhXk2W8dYuK5",
-      "include_colab_link": true
+      "gpuType": "T4",
+      "include_colab_link": true,
+      "provenance": []
     },
     "kernelspec": {
       "display_name": "Python 3",
       "name": "python3"
     },
     "language_info": {
-      "name": "python"
+      "codemirror_mode": {
+        "name": "ipython",
+        "version": 3
+      },
+      "file_extension": ".py",
+      "mimetype": "text/x-python",
+      "name": "python",
+      "nbconvert_exporter": "python",
+      "pygments_lexer": "ipython3",
+      "version": "3.11.4"
     },
     "widgets": {
       "application/vnd.jupyter.widget-state+json": {
         "142c94d6f7b54cdca12596df1892e09d": {
           "model_module": "@jupyter-widgets/controls",
-          "model_name": "HBoxModel",
           "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
           "state": {
             "_dom_classes": [],
             "_model_module": "@jupyter-widgets/controls",
@@ -303,76 +284,10 @@
             "layout": "IPY_MODEL_b1e1ba1085734f3a9fbd242c8a6080a9"
           }
         },
-        "34f4c1e6cadf49b0ba0dcfcdd47b43bb": {
-          "model_module": "@jupyter-widgets/controls",
-          "model_name": "HTMLModel",
-          "model_module_version": "1.5.0",
-          "state": {
-            "_dom_classes": [],
-            "_model_module": "@jupyter-widgets/controls",
-            "_model_module_version": "1.5.0",
-            "_model_name": "HTMLModel",
-            "_view_count": null,
-            "_view_module": "@jupyter-widgets/controls",
-            "_view_module_version": "1.5.0",
-            "_view_name": "HTMLView",
-            "description": "",
-            "description_tooltip": null,
-            "layout": "IPY_MODEL_1b5c12306a3946148af361aaf9735645",
-            "placeholder": "​",
-            "style": "IPY_MODEL_ff4431bd2c2b4116832bb71354bb6d35",
-            "value": "Q4_K_M.gguf: 100%"
-          }
-        },
-        "a978ccabd6234580a5a7af7bb6ae8555": {
-          "model_module": "@jupyter-widgets/controls",
-          "model_name": "FloatProgressModel",
-          "model_module_version": "1.5.0",
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-            "_model_module": "@jupyter-widgets/controls",
-            "_model_module_version": "1.5.0",
-            "_model_name": "FloatProgressModel",
-            "_view_count": null,
-            "_view_module": "@jupyter-widgets/controls",
-            "_view_module_version": "1.5.0",
-            "_view_name": "ProgressView",
-            "bar_style": "success",
-            "description": "",
-            "description_tooltip": null,
-            "layout": "IPY_MODEL_65525d3928244f2c9c7a6119187094ba",
-            "max": 1630263008,
-            "min": 0,
-            "orientation": "horizontal",
-            "style": "IPY_MODEL_c61beea272824cd58303315783fe8da0",
-            "value": 1630263008
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-        "99bdbf2d528048c1a2c6b4ce9e984603": {
-          "model_module": "@jupyter-widgets/controls",
-          "model_name": "HTMLModel",
-          "model_module_version": "1.5.0",
-          "state": {
-            "_dom_classes": [],
-            "_model_module": "@jupyter-widgets/controls",
-            "_model_module_version": "1.5.0",
-            "_model_name": "HTMLModel",
-            "_view_count": null,
-            "_view_module": "@jupyter-widgets/controls",
-            "_view_module_version": "1.5.0",
-            "_view_name": "HTMLView",
-            "description": "",
-            "description_tooltip": null,
-            "layout": "IPY_MODEL_aa9f16e7642e430589494c2c20c46359",
-            "placeholder": "​",
-            "style": "IPY_MODEL_4a94205967d94274bae21112ad03c8e0",
-            "value": " 1.63G/1.63G [00:34&lt;00:00, 53.8MB/s]"
-          }
-        },
-        "b1e1ba1085734f3a9fbd242c8a6080a9": {
+        "1b5c12306a3946148af361aaf9735645": {
           "model_module": "@jupyter-widgets/base",
-          "model_name": "LayoutModel",
           "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
           "state": {
             "_model_module": "@jupyter-widgets/base",
             "_model_module_version": "1.2.0",
@@ -421,10 +336,46 @@
             "width": null
           }
         },
-        "1b5c12306a3946148af361aaf9735645": {
+        "34f4c1e6cadf49b0ba0dcfcdd47b43bb": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_1b5c12306a3946148af361aaf9735645",
+            "placeholder": "​",
+            "style": "IPY_MODEL_ff4431bd2c2b4116832bb71354bb6d35",
+            "value": "Q4_K_M.gguf: 100%"
+          }
+        },
+        "4a94205967d94274bae21112ad03c8e0": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "65525d3928244f2c9c7a6119187094ba": {
           "model_module": "@jupyter-widgets/base",
-          "model_name": "LayoutModel",
           "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
           "state": {
             "_model_module": "@jupyter-widgets/base",
             "_model_module_version": "1.2.0",
@@ -473,25 +424,55 @@
             "width": null
           }
         },
-        "ff4431bd2c2b4116832bb71354bb6d35": {
+        "99bdbf2d528048c1a2c6b4ce9e984603": {
           "model_module": "@jupyter-widgets/controls",
-          "model_name": "DescriptionStyleModel",
           "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
           "state": {
+            "_dom_classes": [],
             "_model_module": "@jupyter-widgets/controls",
             "_model_module_version": "1.5.0",
-            "_model_name": "DescriptionStyleModel",
+            "_model_name": "HTMLModel",
             "_view_count": null,
-            "_view_module": "@jupyter-widgets/base",
-            "_view_module_version": "1.2.0",
-            "_view_name": "StyleView",
-            "description_width": ""
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
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+            "_view_module": "@jupyter-widgets/controls",
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+            "bar_style": "success",
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+            "description_tooltip": null,
+            "layout": "IPY_MODEL_65525d3928244f2c9c7a6119187094ba",
+            "max": 1630263008,
+            "min": 0,
+            "orientation": "horizontal",
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@@ -540,26 +521,10 @@
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@@ -608,10 +573,26 @@
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+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
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+            "_view_module": "@jupyter-widgets/base",
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@@ -628,4 +609,4 @@
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\ No newline at end of file
+}