Alternatives and similar repositories for llm-fine-tuning

Users that are interested in llm-fine-tuning are comparing it to the libraries listed below

• anyscale / ray-summit-2023-training
  ☆87Updated last year
• anyscale / Made-With-ML
  ☆27Updated 2 years ago
• davidmirror-ops / flyte-the-hard-way
  Prepare requirements and deploy Flyte using Helm
  ☆74Updated 3 months ago
• flyteorg / flytesnacks
  Flyte Documentation 📖
  ☆83Updated 4 months ago
• dmatrix / ray-core-tutorial
  Introduction to Ray Core Design Patterns and APIs.
  ☆71Updated last year
• unionai-oss / unionml
  UnionML: the easiest way to build and deploy machine learning microservices
  ☆335Updated last year
• flyteorg / flytelab
  Machine Learning Projects with Flytekit
  ☆37Updated 2 years ago
• anyscale / e2e-llm-workflows
  Fine-tune an LLM to perform batch inference and online serving.
  ☆112Updated 2 months ago
• jacopotagliabue / post-modern-stack
  Joining the modern data stack with the modern ML stack
  ☆198Updated 2 years ago
• rocket9-code / mlflow-deployment-controller
  Listens MLFlow model registry changes and deploy models based on configurations
  ☆21Updated 2 years ago
• dm4ml / gate
  Drift detection module for machine learning pipelines.
  ☆25Updated 2 years ago
• zenml-io / mlstacks
  A series of Terraform based recipes to provision popular MLOps stacks on the cloud.
  ☆255Updated 9 months ago
• zenml-io / zenml-gitflow
  A repository that showcases how you can use ZenML with Git
  ☆69Updated 2 months ago
• adriangonz / mlflow-talk
  End to End example integrating MLFlow and Seldon Core
  ☆52Updated 4 years ago
• outerbounds / metaflow-tools
  Tools and utilities for operating Metaflow in production
  ☆59Updated this week
• astronomer / ask-astro
  An end-to-end LLM reference implementation providing a Q&A interface for Airflow and Astronomer
  ☆255Updated 3 weeks ago
• scalingpythonml / scaling-python-with-ray
  Serverless Python with Ray
  ☆57Updated 2 years ago
• alvarobartt / vertex-ai-huggingface
  🤗 Collection of examples on how to train, deploy and monitor HuggingFace models in Google Cloud Vertex AI
  ☆21Updated last year
• trubrics / trubrics-python
  Product analytics for AI Assistants
  ☆155Updated 2 months ago
• evidentlyai / community-examples
  Examples of using Evidently to evaluate, test and monitor ML models.
  ☆34Updated last month
• daddydrac / Deep-Learning-Ultra
  Open source Deep Learning Containers (DLCs) are a set of Docker images for training and serving models in PyTorch, OpenCV (compiled for G…
  ☆85Updated last year
• scalingpythonml / scalingpythonml
  Scaling Python Machine Learning
  ☆47Updated last year
• sayakpaul / ml-deployment-k8s-fastapi
  This project shows how to serve an ONNX-optimized image classification model as a web service with FastAPI, Docker, and Kubernetes.
  ☆217Updated 3 years ago
• chassisml / chassis
  Chassis turns machine learning models into portable container images that can run just about anywhere.
  ☆86Updated last year
• ray-project / ray-educational-materials
  This is suite of the hands-on training materials that shows how to scale CV, NLP, time-series forecasting workloads with Ray.
  ☆422Updated last year
• mlops-guide / dvc-gitactions
  Example project with a complete MLOps cycle: versioning data, generating reports on pull requests and deploying the model on releases wit…
  ☆48Updated 3 years ago
• mlrun / demos
  End to end MLRun demos
  ☆92Updated 2 months ago
• lakshmanok / generative-ai-design-patterns
  A catalog of design patterns when building generative AI applications
  ☆176Updated last week
• jacopotagliabue / recs-at-resonable-scale
  Recommendations at "Reasonable Scale": joining dataOps with recSys through dbt, Merlin and Metaflow
  ☆238Updated 2 years ago
• getindata / kedro-kubeflow
  Kedro Plugin to support running workflows on Kubeflow Pipelines
  ☆54Updated last month