Update Llama2_Gradio.ipynb

f5e0ebdb · sekyonda · bc2d45aa · f5e0ebdb
Commit f5e0ebdb authored 1 year ago by sekyonda
--- a/demo_apps/Llama2_Gradio.ipynb
+++ b/demo_apps/Llama2_Gradio.ipynb
@@ -16,7 +16,7 @@
    "\n",
    "**Note** After the free trial ends, you will need to enter billing info to continue to use Llama2 hosted on Replicate.\n",
    "\n",
-    "To tun this example:\n",
+    "To run this example:\n",
    "- Set up your Replicate API token and enter it in place of `<your replicate api token>`\n",
    "- Run the notebook\n",
    "- Enter your question and click Submit\n",

 %% Cell type:markdown id:47a9adb3 tags:

 ## This demo app shows how to query Llama 2 using the Gradio UI.

 Since we are using Replicate in this example, you will need to replace `<your replicate api token>` with your API token.

 To get the Replicate token:

 - You will need to first sign in with Replicate with your github account
 - Then create a free API token [here](https://replicate.com/account/api-tokens) that you can use for a while.

 **Note** After the free trial ends, you will need to enter billing info to continue to use Llama2 hosted on Replicate.

-To tun this example:
+To run this example:
 - Set up your Replicate API token and enter it in place of `<your replicate api token>`
 - Run the notebook
 - Enter your question and click Submit

 In the notebook or a browser with URL http://127.0.0.1:7860 you should see a UI with your answer.

 %% Cell type:code id:928041cc tags:

 ``` python
 from langchain.schema import AIMessage, HumanMessage
 import gradio as gr
 from langchain.llms import Replicate
 import os

 os.environ["REPLICATE_API_TOKEN"] = "<your replicate api token>"

 llama2_13b_chat = "meta/llama-2-13b-chat:f4e2de70d66816a838a89eeeb621910adffb0dd0baba3976c96980970978018d"

 llm = Replicate(
    model=llama2_13b_chat,
    model_kwargs={"temperature": 0.01, "top_p": 1, "max_new_tokens":500}
 )


 def predict(message, history):
    history_langchain_format = []
    for human, ai in history:
        history_langchain_format.append(HumanMessage(content=human))
        history_langchain_format.append(AIMessage(content=ai))
    history_langchain_format.append(HumanMessage(content=message))
    gpt_response = llm(message) #history_langchain_format)
    return gpt_response#.content

 gr.ChatInterface(predict).launch()
 ```

 %% Output

    Init param `input` is deprecated, please use `model_kwargs` instead.

    Running on local URL:  http://127.0.0.1:7860
    
    To create a public link, set `share=True` in `launch()`.