02-open-source/homework.ipynb

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   "source": [
    "### 1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "```\n",
    "ollama version is 0.1.48\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "{\n",
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  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> Sure, here is the answer:\n",
    "> \n",
    "> 10 * 10 = 100"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "```\n",
    "docker run -it \\\n",
    "    --rm \\\n",
    "    -v $(pwd)/ollama_files:/root/.ollama \\\n",
    "    -p 11434:11434 \\\n",
    "    --name ollama \\\n",
    "    ollama/ollama\n",
    "```\n",
    "\n",
    "1.7 G"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "```\n",
    "FROM ollama/ollama\n",
    "\n",
    "COPY ollama_files /root/.ollama\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 6"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "prompt = \"What's the formula for energy?\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from openai import OpenAI\n",
    "\n",
    "client = OpenAI(\n",
    "    base_url=\"http://localhost:11434/v1/\",\n",
    "    api_key=\"ollama\",\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "response = client.chat.completions.create(\n",
    "    model=\"gemma:2b\", messages=[{\"role\": \"user\", \"content\": prompt}], temperature=0.0\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Sure, here's the formula for energy:\n",
      "\n",
      "**E = K + U**\n",
      "\n",
      "Where:\n",
      "\n",
      "* **E** is the energy in joules (J)\n",
      "* **K** is the kinetic energy in joules (J)\n",
      "* **U** is the potential energy in joules (J)\n",
      "\n",
      "**Kinetic energy (K)** is the energy an object possesses when it moves or is in motion. It is calculated as half the product of an object's mass (m) and its velocity (v) squared:\n",
      "\n",
      "**K = 1/2mv^2**\n",
      "\n",
      "**Potential energy (U)** is the energy an object possesses due to its position or configuration. It is calculated as the product of an object's mass, gravitational constant (g), and height or position above a reference point.\n",
      "\n",
      "**U = mgh**\n",
      "\n",
      "Where:\n",
      "\n",
      "* **m** is the mass in kilograms (kg)\n",
      "* **g** is the gravitational constant (9.8 m/s^2)\n",
      "* **h** is the height or position in meters (m)\n",
      "\n",
      "The formula shows that energy can be expressed as the sum of kinetic and potential energy. The kinetic energy is a measure of the object's ability to do work, while the potential energy is a measure of the object's ability to do work against a force.\n"
     ]
    }
   ],
   "source": [
    "answer = response.choices[0].message.content\n",
    "print(answer)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "CompletionUsage(completion_tokens=281, prompt_tokens=0, total_tokens=281)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "response.usage"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "f704a5f197e3420b8fb475e5761d1b94",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "tokenizer_config.json:   0%|          | 0.00/33.6k [00:00<?, ?B/s]"
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     "output_type": "display_data"
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    {
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      },
      "text/plain": [
       "tokenizer.model:   0%|          | 0.00/4.24M [00:00<?, ?B/s]"
      ]
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    {
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      "text/plain": [
       "tokenizer.json:   0%|          | 0.00/17.5M [00:00<?, ?B/s]"
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       "model_id": "76342fe302af4444998413e44921efe1",
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      "text/plain": [
       "special_tokens_map.json:   0%|          | 0.00/636 [00:00<?, ?B/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from transformers import AutoTokenizer\n",
    "\n",
    "access_token = \"\"\n",
    "tokenizer = AutoTokenizer.from_pretrained(\"google/gemma-2b\", token=access_token)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "281"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(tokenizer(answer)[\"input_ids\"])"
   ]
  }
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