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community-amp-catalog-default.yaml
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community-amp-catalog-default.yaml
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name: Community
entries:
- title: Contextual Chatbot with NeMo Guardrails
label: CML_AMP_NeMo-Guardrails-Chatbot
short_description: |
This Applied Machine Learning Prototype (AMP) is a similarity-search chatbot that demonstrates safe and responsible AI use for organizations through customizable guardrails.
long_description: |
This Applied Machine Learning Prototype (AMP) builds a similarity-search based chatbot built using Langchain, OpenAI embeddings, Pinecone Vector DB, and NeMo-Guardrails. This chatbot is designed to showcase how organizations can leverage AI safely and responsibly by implementing guardrails.
long_description_html: |
This Applied Machine Learning Prototype (AMP) builds a similarity-search based chatbot built using Langchain, OpenAI embeddings, Pinecone Vector DB, and NeMo-Guardrails. This chatbot is designed to showcase how organizations can leverage AI safely and responsibly by implementing guardrails.
image_path: >-
https://raw.githubusercontent.com/kevinbtalbert/CML_AMP_NeMo-Guardrails-Chatbot/main/assets/demo.png
tags:
- NeMo Guardrails
- Secure AI
- OpenAI
- Langchain
- Pinecone
- Streamlit
- NVIDIA Rails
- Chatbot
git_url: 'https://github.com/kevinbtalbert/CML_AMP_NeMo-Guardrails-Chatbot.git'
is_prototype: true
is_community: true
is_new: true
- title: CML HuggingFace Models
label: cml_hf_models
short_description: |
Choose any 7B or 13B LLM from HuggingFace and deploy as a CML Model.
long_description: |
Choose any 7B or 13B LLM from HuggingFace and deploy as a CML Model. Cloudera Machine Learning models expose an Inference endpoint for users to access and communicate with. The AMP creates a Gradio App UI which can be used to interact with the deployed CML Model.
long_description_html: |
Choose any 7B or 13B LLM from HuggingFace and deploy as a CML Model. Cloudera Machine Learning models expose an Inference endpoint for users to access and communicate with. The AMP creates a Gradio App UI which can be used to interact with the deployed CML Model.
image_path: >-
https://raw.githubusercontent.com/nkityd09/cml_hf_models/main/images/cml_hf_ui.png
tags:
- huggingface
- 7B
- 13V
git_url: 'https://github.com/nkityd09/cml_hf_models.git'
is_prototype: true
is_community: true
is_new: true
- title: Text to Image Using Stable Diffusion
label: CML_AMP-Text-to-Image-with-Stable-Diffusion
short_description: |
Run a browser interface based on Gradio library for Stable Diffusion within the CML platform.
long_description: |
Run a browser interface based on Gradio library for Stable Diffusion within the CML platform.
long_description_html: |
Run a browser interface based on Gradio library for Stable Diffusion within the CML platform.
image_path: >-
https://raw.githubusercontent.com/kevinbtalbert/CML_AMP-Text-to-Image-with-Stable-Diffusion/master/catalog-entry.png
tags:
- Text2Image
- Stable Diffusion
git_url: 'https://github.com/kevinbtalbert/CML_AMP-Text-to-Image-with-Stable-Diffusion.git'
is_prototype: true
is_community: true
is_new: true
- title: Text Summarization using IBM watsonx.ai
label: CML_AMP_watsonxai
short_description: |
This repository demonstrates how to use watson machine learning Python SDK to call watsonx.ai models from Cloudera Machine Learning (CML) workspace.
long_description: |
This repository demonstrates how to use watson machine learning Python SDK to call watsonx.ai models from Cloudera Machine Learning (CML) workspace.
long_description_html: |
This repository demonstrates how to use watson machine learning Python SDK to call watsonx.ai models from Cloudera Machine Learning (CML) workspace.
image_path: >-
https://raw.githubusercontent.com/agupta-git/CML_AMP_watsonxai/main/assets/app_interface.png
tags:
- watsonx
- Text Summarization
- IBM
git_url: 'https://github.com/agupta-git/CML_AMP_watsonxai.git'
is_prototype: true
is_community: true
is_new: true
- title: Ray on CML QuickStart
label: ray
short_description: A series of starter notebooks that demonstrate how to use Ray on CML
long_description: >-
A series of starter notebooks that demonstrate how to launch a Ray cluster, use python libraries, train and deploy a model using Ray Tune in CML.
image_path: >-
https://github.com/vidushisomani/CML_Ray_Starter_AMP/blob/main/images/amp-cover.png?raw=true
tags:
- Ray
git_url: "https://github.com/vidushisomani/CML_Ray_Starter_AMP.git"
is_prototype: true
is_community: true
is_new: true