Need help in Deployment of TheBloke/vicuna-13B-v1.5-GGUF model on AWS

Deploy this TheBloke/vicuna-13B-v1.5-GGUF model on AWS

I want to use this model as an endpoint in my web application in this format:

Chatbot Requirements

  1. Scope: Chatbot (Encoder/Decoder for Text Inference or Conversational)
  2. Input via API (JSON): Chatgpt Style – The template can be see below

The JSON will contain 25 user messages, and the response should be the system response.
Please use this guidelines to understand API consumption: InvokeEndpoint - Amazon SageMaker

  1. Prompt Template for the system:
    a. template = ‘’’
    You are going to be my education assistant.

  2. LLM Model Parameters: max_new_tokens=512, temperature=0.7, top_p=0.9

  3. If possible use a AutomodelforCausalLM otherwise train a LLM model.

  4. It will be deployed on AWS Sagemaker using S3 buckets.

  5. The GGUF should be saved on a S3 Bucket.

  6. Chat Buffer should store 25 conversations and create a session ID (No need to send this to the End point).

  7. The quantized model is contained here vicuna-13b-v1.5.Q4_K_M.gguf · TheBloke/vicuna-13B-v1.5-GGUF at main

  8. Use HuggingFace/Langchain when possible.

  9. Deliverables: Jupyter notebook/Code – 2 Hours should be used to set up the model in AWS with the customer.

Provide me with complete source code that I can use in my jupyter notebook on aws to make an endpoint.
I need it asap.