Mixtral 8x7B

artitw · Feb 10, 2024 · dac86f5 · dac86f5
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diff --git a/README.md b/README.md
@@ -36,7 +36,6 @@ Transform texts in a hundred different [languages](https://github.com/artitw/tex
 
 ## Colab Notebooks
 * Assistant (free private ChatGPT LLM alternative) [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1K6Kk80w9vjFZ7PL9dPRgVuOPuaWcY4ae?usp=sharing)
-* Assistant with knowledge base [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1hkNgpSmmUA-mzUibqz25xq-E8KYOLuVx?usp=sharing)
 * STF-IDF multilingual search [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1RaWj5SqWvyC2SsCTGg8IAVcl9G5hOB50?usp=sharing)
 * All examples [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1LE_ifTpOGO5QJCKNQYtZe6c_tjbwnulR)
 
@@ -193,29 +192,8 @@ t2t.Transformer.LANGUAGES
 ```
 import text2text as t2t
 asst = t2t.Assistant()
-instructions = "Generate a JSON object that maps English characters as keys and Greek equivalents as values: {"
-res = asst.transform([instructions])
-#[
-#  '{\n"a": "α",\n"b": "β",\n"c": "γ",\n"d": "δ",\n"e": "ε",\n"f": "φ",\n"g": "χ",\n"h": "ι",\n"i": "η",\n"j": "κ",\n"k": "λ",\n"l": "μ",\n"m": "ν",\n"n": "ξ",\n"o": "ο",\n"p": "π",\n"q": "ρ",\n"r": "σ",\n"s": "τ",\n"t": "υ",\n"u": "ύ",\n"v": "φ",\n"w": "χ",\n"x": "ψ",\n"y": "ω",\n"z": "ζ"\n}'
-#]
-
-#OpenAI Completion API
-
-prompt = """
-I have a clove of garlic, some brown rice, a few baby bok choy,
-some olive oil, and a few slices of bacon.
-How can I prepare a meal our of these ingredients?
-"""
-
-input_prompts = [prompt]
-num_tokens = asst.completion_tokens(input_prompts)
-print(num_tokens[0])
-
-results = asst.completion(input_prompts)
-print(results[0])
 
 #OpenAI Chat Completion API
-
 chat_history = [
     {"role": "user",  "content": "Hi"},
     {"role": "assistant", "content": "Hello, how are you?"},
@@ -227,8 +205,6 @@ print(num_tokens)
 result = asst.chat_completion(chat_history, stream=True) #{'role': 'assistant', 'content': '1. Make a list of things to be grateful for.\n2. Go outside and take a walk in nature.\n3. Practice mindfulness meditation.\n4. Connect with a loved one or friend.\n5. Do something kind for someone else.\n6. Engage in a creative activity like drawing or writing.\n7. Read an uplifting book or listen to motivational podcasts.'}
 print(result["content"])
 ```
-- To use a dynamic knowledge base, see [![Q&A Assistant Demo](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1hkNgpSmmUA-mzUibqz25xq-E8KYOLuVx?usp=sharing)
-- To use with LangChain, see [![LangChain integration](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1K6Kk80w9vjFZ7PL9dPRgVuOPuaWcY4ae?usp=sharing)
 
 ### Tokenization
 ```

diff --git a/demos/[Text2Text]_Demo_All.ipynb → demos/Text2Text_Demos.ipynb b/demos/[Text2Text]_Demo_All.ipynb → demos/Text2Text_Demos.ipynb
@@ -64,31 +64,27 @@
         "# Run at no cost on Google Colab free tier, so you don't even need your own device.\n",
         "# To add a knowledge base, see https://colab.research.google.com/drive/1hkNgpSmmUA-mzUibqz25xq-E8KYOLuVx?usp=sharing\n",
         "\n",
-        "assistant = t2t.Assistant()\n",
-        "assistant.transform([\"Describe Text2Text in a few words: \"])\n",
-        "#['Text2Text is an AI-powered text generation tool that creates coherent and continuous text based on prompts.']"
+        "asst = t2t.Assistant()\n",
+        "\n",
+        "#OpenAI Chat Completion API\n",
+        "\n",
+        "chat_history = [\n",
+        "    {\"role\": \"user\",  \"content\": \"Hi\"},\n",
+        "    {\"role\": \"assistant\", \"content\": \"Hello, how are you?\"},\n",
+        "    {\"role\": \"user\", \"content\": \"What should I do today?\"}\n",
+        "]\n",
+        "num_tokens = asst.chat_completion_tokens(chat_history) #31\n",
+        "print(num_tokens)\n",
+        "\n",
+        "result = asst.chat_completion(chat_history, stream=True) #{'role': 'assistant', 'content': '1. Make a list of things to be grateful for.\\n2. Go outside and take a walk in nature.\\n3. Practice mindfulness meditation.\\n4. Connect with a loved one or friend.\\n5. Do something kind for someone else.\\n6. Engage in a creative activity like drawing or writing.\\n7. Read an uplifting book or listen to motivational podcasts.'}\n",
+        "print(result[\"content\"])"
       ],
       "metadata": {
         "id": "VPMdUSy9YYRl"
       },
       "execution_count": null,
       "outputs": []
     },
-    {
-      "cell_type": "code",
-      "source": [
-        "instructions = \"Generate a JSON object that maps English characters as keys and Greek equivalents as values: {\"\n",
-        "assistant.transform([instructions])\n",
-        "# [\n",
-        "#  '{\\n\"a\": \"α\",\\n\"b\": \"β\",\\n\"c\": \"γ\",\\n\"d\": \"δ\",\\n\"e\": \"ε\",\\n\"f\": \"φ\",\\n\"g\": \"χ\",\\n\"h\": \"ι\",\\n\"i\": \"η\",\\n\"j\": \"κ\",\\n\"k\": \"λ\",\\n\"l\": \"μ\",\\n\"m\": \"ν\",\\n\"n\": \"ξ\",\\n\"o\": \"ο\",\\n\"p\": \"π\",\\n\"q\": \"ρ\",\\n\"r\": \"σ\",\\n\"s\": \"τ\",\\n\"t\": \"υ\",\\n\"u\": \"ύ\",\\n\"v\": \"φ\",\\n\"w\": \"χ\",\\n\"x\": \"ψ\",\\n\"y\": \"ω\",\\n\"z\": \"ζ\"\\n}'\n",
-        "# ]"
-      ],
-      "metadata": {
-        "id": "TaEBdeQMXPzb"
-      },
-      "execution_count": null,
-      "outputs": []
-    },
     {
       "cell_type": "code",
       "source": [