diff --git a/ch2/jupyter-notebooks/interacting-with-llms-haystack2.0.ipynb b/ch2/jupyter-notebooks/interacting-with-llms-haystack2.0.ipynb
index e630dd9..dfce2de 100644
--- a/ch2/jupyter-notebooks/interacting-with-llms-haystack2.0.ipynb
+++ b/ch2/jupyter-notebooks/interacting-with-llms-haystack2.0.ipynb
@@ -40,7 +40,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -61,7 +61,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -83,36 +83,53 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [],
    "source": [
-    "prompt_template = \"\"\"\n",
-    "        Given a question, you provide a short answer.\n",
-    "        \\nQuestion: {{question}}\n",
-    "        \\nAnswer:\n",
-    "        \"\"\"\n"
+    "gpt = GPTGenerator(api_key=os.getenv(\"OPENAI_API_KEY\"),  \n",
+    "                                                  model_name='gpt-4', \n",
+    "                                                  api_base_url = 'https://api.openai.com/v1',\n",
+    "                                                  )"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 6,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'replies': ['The capital of France is Paris.'],\n",
+       " 'metadata': [{'model': 'gpt-4-0613',\n",
+       "   'index': 0,\n",
+       "   'finish_reason': 'stop',\n",
+       "   'usage': {'prompt_tokens': 25,\n",
+       "    'completion_tokens': 7,\n",
+       "    'total_tokens': 32}}]}"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "gpt = GPTGenerator(api_key=os.getenv(\"OPENAI_API_KEY\"),  \n",
-    "                                                  model_name='gpt-4', \n",
-    "                                                  api_base_url = 'https://api.openai.com/v1',\n",
-    "                                                  )"
+    "gpt.run(\"You are a helpful assistant who provides answers to questions. What is the capital of France?\")"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [],
    "source": [
-    "gpt.run(\"Who lives in Paris?\")"
+    "prompt_template = \"\"\"\n",
+    "        Given a question, you provide a short answer.\n",
+    "        \\nQuestion: {{question}}\n",
+    "        \\nAnswer:\n",
+    "        \"\"\"\n"
    ]
   },
   {
@@ -207,7 +224,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "question = \"Who is the smartest man in the universe\"\n",
+    "question = \"You are a helpful assistant who provides answers to questions. What is the capital of France?\"\n",
     "result = hf_pipeline.run(\n",
     "    {\n",
     "        \"prompt_builder\": {\"question\": question},\n",
@@ -240,8 +257,6 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "\n",
-    "\n",
     "from scripts.huggingfaceendpoints import InferenceEndpointAPI"
    ]
   },
@@ -283,13 +298,20 @@
     "mistral_pipeline.draw( \"pipeline-diagrams/mistral-pipeline.png\")"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
-    "question = \"What is the capital of France?\"\n",
+    "question = \"What is the capital of Rome?\"\n",
     "result = mistral_pipeline.run(\n",
     "    {\n",
     "        \"prompt_builder\": {\"question\": question},\n",
diff --git a/ch2/jupyter-notebooks/interacting-with-llms-hugging-face.ipynb b/ch2/jupyter-notebooks/interacting-with-llms-hugging-face.ipynb
index 633047c..d7b8f52 100644
--- a/ch2/jupyter-notebooks/interacting-with-llms-hugging-face.ipynb
+++ b/ch2/jupyter-notebooks/interacting-with-llms-hugging-face.ipynb
@@ -47,80 +47,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "2527b40cc0134ed2b7e5d27f804755f3",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "Downloading (…)okenizer_config.json:   0%|          | 0.00/199 [00:00<?, ?B/s]"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "d853bb35ec4742e2830a39062de02785",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "Downloading tokenizer.json:   0%|          | 0.00/14.5M [00:00<?, ?B/s]"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "22d8e2038d064db79eed6d05c7b5cf8e",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "Downloading (…)cial_tokens_map.json:   0%|          | 0.00/85.0 [00:00<?, ?B/s]"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "67c7cda044b5420ebb19be2e9a1d2a1e",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "Downloading (…)lve/main/config.json:   0%|          | 0.00/715 [00:00<?, ?B/s]"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "32ec5cd195004c8ea4d598a07cc2596e",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "Downloading model.safetensors:   0%|          | 0.00/6.01G [00:00<?, ?B/s]"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "from transformers import AutoModelForCausalLM, AutoTokenizer\n",
     "\n",
@@ -221,25 +150,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/Users/macpro/anaconda3/envs/llm-pipelines/lib/python3.10/site-packages/bitsandbytes/cextension.py:34: UserWarning: The installed version of bitsandbytes was compiled without GPU support. 8-bit optimizers, 8-bit multiplication, and GPU quantization are unavailable.\n",
-      "  warn(\"The installed version of bitsandbytes was compiled without GPU support. \"\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "'NoneType' object has no attribute 'cadam32bit_grad_fp32'\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": []
   },
   {
@@ -330,6 +243,42 @@
     "trainer.model.save_pretrained(peft_model_id) \n",
     "tokenizer.save_pretrained(peft_model_id) "
    ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Connecting to a model through inference end points: MistralAI\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import requests\n",
+    "import os \n",
+    "from dotenv import load_dotenv\n",
+    "\n",
+    "load_dotenv()\n",
+    "# Applicable only if your env file is stored two levels above the current directory\n",
+    "load_dotenv(\"./../../.env\")\n",
+    "\n",
+    "hugging_face_token_endpoint = os.getenv(\"mistral_hf_token\")\n",
+    "API_URL = \"https://api-inference.huggingface.co/models/mistralai/Mistral-7B-Instruct-v0.1\"\n",
+    "headers = {\"Authorization\": f\"Bearer {hugging_face_token_endpoint}\"}\n",
+    "\n",
+    "def query(payload):\n",
+    "\tresponse = requests.post(API_URL, headers=headers, json=payload)\n",
+    "\treturn response.json()\n",
+    "\t\n",
+    "output = query({\n",
+    "\t\"inputs\": \"You are a helpful assistant who provides answers to questions. What is the capital of France?\",\n",
+    "})\n",
+    "\n",
+    "print(output)"
+   ]
   }
  ],
  "metadata": {
diff --git a/ch2/jupyter-notebooks/interacting-with-llms-openai.ipynb b/ch2/jupyter-notebooks/interacting-with-llms-openai.ipynb
index ebb9c52..6244ac3 100644
--- a/ch2/jupyter-notebooks/interacting-with-llms-openai.ipynb
+++ b/ch2/jupyter-notebooks/interacting-with-llms-openai.ipynb
@@ -16,7 +16,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -34,7 +34,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -63,20 +63,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "{\n",
-      "  \"role\": \"assistant\",\n",
-      "  \"content\": \"Hello! I can definitely help you with that. You can find Colombian coffee in various places. One option is to check your local grocery store or coffee shop. They often carry Colombian coffee brands. Additionally, you can also consider checking online retailers that specialize in coffee. They usually have a wide selection of Colombian coffee available for purchase.  Is there anything else I can assist you with?\"\n",
-      "}\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "system_prompt = \"\"\" \n",
     "You are a helpful assistant who is knowledgeable about coffee. You are helpful to users who are seeking information about coffee.  \n",
@@ -101,6 +90,31 @@
     "\n",
     "print(completion.choices[0].message) "
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "print(completion.choices[0].message.content)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "completion.keys()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
diff --git a/poetry.lock b/poetry.lock
index cfc5cdc..58b1351 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -623,6 +623,35 @@ files = [
 [package.dependencies]
 colorama = {version = "*", markers = "platform_system == \"Windows\""}
 
+[[package]]
+name = "cmake"
+version = "3.27.7"
+description = "CMake is an open-source, cross-platform family of tools designed to build, test and package software"
+optional = false
+python-versions = "*"
+files = [
+    {file = "cmake-3.27.7-py2.py3-none-macosx_10_10_universal2.macosx_10_10_x86_64.macosx_11_0_arm64.macosx_11_0_universal2.whl", hash = "sha256:d582ef3e9ff0bd113581c1a32e881d1c2f9a34d2de76c93324a28593a76433db"},
+    {file = "cmake-3.27.7-py2.py3-none-manylinux2010_i686.manylinux_2_12_i686.whl", hash = "sha256:8056c99e371ff57229df2068364d7c32fea716cb53b4675f639edfb62663decf"},
+    {file = "cmake-3.27.7-py2.py3-none-manylinux2010_x86_64.manylinux_2_12_x86_64.whl", hash = "sha256:68983b09de633fc1ce6ab6bce9a25bfa181e41598e7c6bc0a6c0108773ee01cb"},
+    {file = "cmake-3.27.7-py2.py3-none-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:8bd1e1fa4fc8de7605c663d9408dceb649112f855aab05cca31fdb72e4d78364"},
+    {file = "cmake-3.27.7-py2.py3-none-manylinux2014_i686.manylinux_2_17_i686.whl", hash = "sha256:c981aafcca2cd7210bd210ec75710c0f34e1fde1998cdcab812e4133e3ab615d"},
+    {file = "cmake-3.27.7-py2.py3-none-manylinux2014_ppc64le.manylinux_2_17_ppc64le.whl", hash = "sha256:1b9067ce0251cba3d4c018f2e1577ba9078e9c1eff6ad607ad5ce867843d4571"},
+    {file = "cmake-3.27.7-py2.py3-none-manylinux2014_s390x.manylinux_2_17_s390x.whl", hash = "sha256:b8a2fcb619b89d1cce7b52828316de9a1f27f0c90c2e39d1eae886428c8ee8c6"},
+    {file = "cmake-3.27.7-py2.py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:499b38c77d52fb1964dbb38d0228fed246263a181939a8e753fde8ca227c8e1e"},
+    {file = "cmake-3.27.7-py2.py3-none-musllinux_1_1_aarch64.whl", hash = "sha256:2fb48c780f1a6a3d19e785ebbb754be79d369e25a1cb81043fab049e709564da"},
+    {file = "cmake-3.27.7-py2.py3-none-musllinux_1_1_i686.whl", hash = "sha256:7bf96237ba11ce2437dc5e071d96b510120a1be4708c631a64b2f38fb46bbd77"},
+    {file = "cmake-3.27.7-py2.py3-none-musllinux_1_1_ppc64le.whl", hash = "sha256:009058bdf4f488709f38eaa5dd0ef0f89c6b9c6b6edd9d5b475a308ef75f80bb"},
+    {file = "cmake-3.27.7-py2.py3-none-musllinux_1_1_s390x.whl", hash = "sha256:591f6b056527aefec009bc61a388776b2fc62444deb0038112a471031f61aeca"},
+    {file = "cmake-3.27.7-py2.py3-none-musllinux_1_1_x86_64.whl", hash = "sha256:bd40d46dbad3555d5b3ce054bef24b85f256b19139493773751ab6f2b71c1219"},
+    {file = "cmake-3.27.7-py2.py3-none-win32.whl", hash = "sha256:bdbf0256f554f68c7b1d9740f5d059daf875b685c81a479cbe69038e84eb2fb9"},
+    {file = "cmake-3.27.7-py2.py3-none-win_amd64.whl", hash = "sha256:810e592b606d05a3080a9c19ea839b13226f62cae447a22485b2365782f6b926"},
+    {file = "cmake-3.27.7-py2.py3-none-win_arm64.whl", hash = "sha256:72289361866314f73be2ae63ddee224ff70223dcef9feb66d0072bf17e245564"},
+    {file = "cmake-3.27.7.tar.gz", hash = "sha256:9f4a7c7be2a25de5901f045618f41b833ea6c0f647115201d38e4fdf7e2815bc"},
+]
+
+[package.extras]
+test = ["coverage (>=4.2)", "flake8 (>=3.0.4)", "path.py (>=11.5.0)", "pytest (>=3.0.3)", "pytest-cov (>=2.4.0)", "pytest-runner (>=2.9)", "pytest-virtualenv (>=1.7.0)", "scikit-build (>=0.10.0)", "setuptools (>=28.0.0)", "virtualenv (>=15.0.3)", "wheel"]
+
 [[package]]
 name = "colorama"
 version = "0.4.4"
@@ -1698,6 +1727,16 @@ all = ["black", "flake8", "isort", "mdformat", "mypy", "packaging", "pydocstyle"
 checking = ["black", "flake8", "isort", "mdformat", "mypy", "pydocstyle", "pylint", "pylintfileheader"]
 testing = ["packaging", "pytest"]
 
+[[package]]
+name = "lit"
+version = "17.0.3"
+description = "A Software Testing Tool"
+optional = false
+python-versions = "*"
+files = [
+    {file = "lit-17.0.3.tar.gz", hash = "sha256:e6049032462be1e2928686cbd4a6cc5b3c545d83ecd078737fe79412c1f3fcc1"},
+]
+
 [[package]]
 name = "loralib"
 version = "0.1.2"
@@ -2134,6 +2173,139 @@ files = [
     {file = "numpy-1.25.2.tar.gz", hash = "sha256:fd608e19c8d7c55021dffd43bfe5492fab8cc105cc8986f813f8c3c048b38760"},
 ]
 
+[[package]]
+name = "nvidia-cublas-cu11"
+version = "11.10.3.66"
+description = "CUBLAS native runtime libraries"
+optional = false
+python-versions = ">=3"
+files = [
+    {file = "nvidia_cublas_cu11-11.10.3.66-py3-none-manylinux1_x86_64.whl", hash = "sha256:d32e4d75f94ddfb93ea0a5dda08389bcc65d8916a25cb9f37ac89edaeed3bded"},
+    {file = "nvidia_cublas_cu11-11.10.3.66-py3-none-win_amd64.whl", hash = "sha256:8ac17ba6ade3ed56ab898a036f9ae0756f1e81052a317bf98f8c6d18dc3ae49e"},
+]
+
+[package.dependencies]
+setuptools = "*"
+wheel = "*"
+
+[[package]]
+name = "nvidia-cuda-cupti-cu11"
+version = "11.7.101"
+description = "CUDA profiling tools runtime libs."
+optional = false
+python-versions = ">=3"
+files = [
+    {file = "nvidia_cuda_cupti_cu11-11.7.101-py3-none-manylinux1_x86_64.whl", hash = "sha256:e0cfd9854e1f2edaa36ca20d21cd0bdd5dcfca4e3b9e130a082e05b33b6c5895"},
+    {file = "nvidia_cuda_cupti_cu11-11.7.101-py3-none-win_amd64.whl", hash = "sha256:7cc5b8f91ae5e1389c3c0ad8866b3b016a175e827ea8f162a672990a402ab2b0"},
+]
+
+[package.dependencies]
+setuptools = "*"
+wheel = "*"
+
+[[package]]
+name = "nvidia-cuda-nvrtc-cu11"
+version = "11.7.99"
+description = "NVRTC native runtime libraries"
+optional = false
+python-versions = ">=3"
+files = [
+    {file = "nvidia_cuda_nvrtc_cu11-11.7.99-2-py3-none-manylinux1_x86_64.whl", hash = "sha256:9f1562822ea264b7e34ed5930567e89242d266448e936b85bc97a3370feabb03"},
+    {file = "nvidia_cuda_nvrtc_cu11-11.7.99-py3-none-manylinux1_x86_64.whl", hash = "sha256:f7d9610d9b7c331fa0da2d1b2858a4a8315e6d49765091d28711c8946e7425e7"},
+    {file = "nvidia_cuda_nvrtc_cu11-11.7.99-py3-none-win_amd64.whl", hash = "sha256:f2effeb1309bdd1b3854fc9b17eaf997808f8b25968ce0c7070945c4265d64a3"},
+]
+
+[package.dependencies]
+setuptools = "*"
+wheel = "*"
+
+[[package]]
+name = "nvidia-cuda-runtime-cu11"
+version = "11.7.99"
+description = "CUDA Runtime native Libraries"
+optional = false
+python-versions = ">=3"
+files = [
+    {file = "nvidia_cuda_runtime_cu11-11.7.99-py3-none-manylinux1_x86_64.whl", hash = "sha256:cc768314ae58d2641f07eac350f40f99dcb35719c4faff4bc458a7cd2b119e31"},
+    {file = "nvidia_cuda_runtime_cu11-11.7.99-py3-none-win_amd64.whl", hash = "sha256:bc77fa59a7679310df9d5c70ab13c4e34c64ae2124dd1efd7e5474b71be125c7"},
+]
+
+[package.dependencies]
+setuptools = "*"
+wheel = "*"
+
+[[package]]
+name = "nvidia-cudnn-cu11"
+version = "8.5.0.96"
+description = "cuDNN runtime libraries"
+optional = false
+python-versions = ">=3"
+files = [
+    {file = "nvidia_cudnn_cu11-8.5.0.96-2-py3-none-manylinux1_x86_64.whl", hash = "sha256:402f40adfc6f418f9dae9ab402e773cfed9beae52333f6d86ae3107a1b9527e7"},
+    {file = "nvidia_cudnn_cu11-8.5.0.96-py3-none-manylinux1_x86_64.whl", hash = "sha256:71f8111eb830879ff2836db3cccf03bbd735df9b0d17cd93761732ac50a8a108"},
+]
+
+[package.dependencies]
+setuptools = "*"
+wheel = "*"
+
+[[package]]
+name = "nvidia-cufft-cu11"
+version = "10.9.0.58"
+description = "CUFFT native runtime libraries"
+optional = false
+python-versions = ">=3"
+files = [
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 ]
 
 [package.dependencies]
 numpy = "*"
 pillow = ">=5.3.0,<8.3.dev0 || >=8.4.dev0"
 requests = "*"
-torch = "2.0.1"
+torch = "2.0.0"
 
 [package.extras]
 scipy = ["scipy"]
@@ -4196,6 +4425,43 @@ torchhub = ["filelock", "huggingface-hub (>=0.15.1,<1.0)", "importlib-metadata",
 video = ["av (==9.2.0)", "decord (==0.6.0)"]
 vision = ["Pillow (<10.0.0)"]
 
+[[package]]
+name = "triton"
+version = "2.0.0"
+description = "A language and compiler for custom Deep Learning operations"
+optional = false
+python-versions = "*"
+files = [
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+    {file = "triton-2.0.0-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:42a0d2c3fc2eab4ba71384f2e785fbfd47aa41ae05fa58bf12cb31dcbd0aeceb"},
+    {file = "triton-2.0.0-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:52c47b72c72693198163ece9d90a721299e4fb3b8e24fd13141e384ad952724f"},
+]
+
+[package.dependencies]
+cmake = "*"
+filelock = "*"
+lit = "*"
+torch = "*"
+
+[package.extras]
+tests = ["autopep8", "flake8", "isort", "numpy", "pytest", "scipy (>=1.7.1)"]
+tutorials = ["matplotlib", "pandas", "tabulate"]
+
 [[package]]
 name = "typing-extensions"
 version = "4.8.0"
@@ -4488,4 +4754,4 @@ multidict = ">=4.0"
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.10"
-content-hash = "c9e80bd08a34403473be58d2b2c55d1c22828adc0205eada1b4625c9f39edb4d"
+content-hash = "969f36a0b9a5ff0dcaf06946b568d9b1e479edb454b71a91224a933f5f87d0c0"
diff --git a/pyproject.toml b/pyproject.toml
index 52ae173..5cdbaed 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -24,7 +24,7 @@ openai = "^0.28.1"
 skypilot = "^0.4.0"
 boto3 = "^1.28.68"
 pytest = "^7.4.2"
-
+torch = ">=2.0.0, !=2.0.1, !=2.1.0"
 
 [build-system]
 requires = ["poetry-core"]