more orchestration tools added

orchestration/banana.yaml

@@ -9,11 +9,11 @@ banana:
   url: https://www.banana.dev/
 
   description: "Banana is a serverless GPU service tailored for AI applications.
-  It allows users to quickly deploy AI models using custom Python framework, connect to data stores, and run inference efficiently.
-  Banana offers built-in CI/CD support, facilitating Docker image creation and deployment on their serverless GPU infrastructure.
-  The service excels in autoscaling applications, minimizing cold boot times to ensure rapid response to changing traffic patterns."
+    It allows users to quickly deploy AI models using custom Python framework, connect to data stores, and run inference efficiently.
+    Banana offers built-in CI/CD support, facilitating Docker image creation and deployment on their serverless GPU infrastructure.
+    The service excels in autoscaling applications, minimizing cold boot times to ensure rapid response to changing traffic patterns."
 
   features:
     - "Efficient GPU Resource Billing."
     - "Dynamic GPU Allocation."
-    - "Rapid Scalable Inference."
+    - "Rapid Scalable Inference."

orchestration/cerebrium.yaml

@@ -0,0 +1,18 @@
+cerebrium:
+  name: "Cerebrium"
+
+  image_url: https://uploads-ssl.webflow.com/63f3d4a9e05fc85e733e1610/63f40e88b105ee11832e827c_full-logo-colour-white-transparent.svg
+
+  tags: 
+    - model-binary
+
+  url: https://www.cerebrium.ai/
+
+  description: "Cerebrium simplifies the process of training, deploying, and monitoring machine learning models using a minimal amount of code.
+    It offers seamless deployment with support for major ML frameworks, including PyTorch, ONNX, and HuggingFace models, as well as prebuilt models optimized for sub-second latency.
+    Additionally, it provides effortless model fine-tuning and monitoring capabilities with integration into top ML observability platforms, enabling alerts about feature or prediction drift, model version comparisons, and in-depth insights into model performance."
+
+  features:
+    - "Serverless GPU Model Deployment."
+    - "Support for All Major Frameworks."
+    - "Automatic Versioning."

orchestration/launchflow.yaml

@@ -0,0 +1,20 @@
+launchflow:
+  name: "LaunchFlow"
+
+  image_url: https://www.launchflow.com/images/logo.svg
+
+  tags: 
+    - model-endpoint
+
+  url: https://www.launchflow.com/
+
+  description: "LaunchFlow is a versatile platform designed for building and deploying real-time applications directly from your code editor.
+    With its seamless integration into popular code editors like VSCode, it allows users to create and deploy applications in less than 60 seconds.
+    This platform is 100% Python-powered and offers a drag-and-drop editor, preloaded templates, connectors for various cloud providers, and VSCode extensions for both local and remote development.
+    LaunchFlow automates cloud infrastructure provisioning from application code, ensuring serverless operation without the need for server management.
+    It offers ready-to-use templates for real-time IoT, machine learning, and security applications, enabling effortless scaling and efficient data analysis."
+
+  features:
+    - "Efficient Deployment."
+    - "Integrated VSCode Extension."
+    - "Serverless Operation."

orchestration/replicate.yaml

@@ -0,0 +1,19 @@
+replicate:
+  name: "Replicate"
+
+  image_url: https://replicate.com/static/favicon.e390e65c9599.png
+
+  tags: 
+    - model-binary
+
+  url: https://replicate.com/
+
+  description: "Replicate offers a simplified approach to running machine learning models at scale, making it accessible even for those without deep machine learning knowledge.
+    Users can run models with just a few lines of code using Replicate's Python library or query the API directly with their preferred tool. The platform hosts a vast library of machine learning models, including language models, video creation and editing models, super resolution models, image restoration models, and more, contributed by the community.
+    Replicate also introduces Cog, an open-source tool for packaging machine learning models in production-ready containers.
+    It streamlines the deployment process, automatically generating scalable API servers for defined models and offering automatic scaling to handle varying traffic loads."
+
+  features:
+    - "Simplified Machine Learning Deployment."
+    - "Extensive Model Library."
+    - "User is billed only for the time their code is running."