huggingface_hub
MLflow
huggingface_hub | MLflow | |
---|---|---|
104 | 56 | |
1,688 | 17,284 | |
4.9% | 1.3% | |
9.6 | 9.9 | |
4 days ago | 6 days ago | |
Python | Python | |
Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
huggingface_hub
-
OpenAI's employees were given two explanations for why Sam Altman was fired
Something to think about:
https://github.com/huggingface/huggingface_hub
- Thoughts on a "Text Generation CivitAI"
-
Civitai alternatives.
Yes! We have a well documented Python library (https://github.com/huggingface/huggingface_hub) and public endpoints (https://huggingface.co/docs/hub/api#endpoints-table) you can use to retrieve information about the models and potentially build UIs with specific use cases in mind
-
Fox Fairy @ Diffusion Forest: Unreal Engine + Stable Diffusion
i think if you search for pixel art here there are some models worth checking out: https://huggingface.co/
- ASK HN: AI is really exciting but where do I start?
- j'ai entraîné une IA à générer Éric Duhaime en clown !
-
[Guide] DreamBooth Training with ShivamShrirao's Repo on Windows Locally
I received another error saying OSError: We couldn't connect to 'https://huggingface.co' to load this model, couldn't find it in the cached files and it looks like ./vae is not the path to a directory containing a file named diffusion_pytorch_model.bin
-
Training a Deep Learning Language Model for Latin text Generation
I plan to release it on https://huggingface.co/, where all this cool AI stuff is available for free for everyone that wishes to try it.
-
Image Upscaling Models Compared (General, Photo and Faces)
For this I used mainly the chainner application with models from here but I also used the google colab automatic1111 stable diffusion webui (for example for Lanczos) and also spaces fromhuggingface like this one or then from the replicate.com website super resolution collection.
-
2D Illustration Styles are scarce on Stable Diffusion so i created a dreambooth model inspired by Hollie Mengert's work
you will now need to create a huggingface account ( https://huggingface.co/) if you haven't already. When you have, go here and accept the terms, https://huggingface.co/runwayml/stable-diffusion-v1-5. When you have done both, click on your profile icon and go to settings. Click access tokens and then create token, name it whatever you want, select "write". When you are finished with all this, then you can run the next cell which is the hugging face cell. It will ask for a token, you copy and paste what you just created.
MLflow
-
Observations on MLOps–A Fragmented Mosaic of Mismatched Expectations
How can this be? The current state of practice in AI/ML work requires adaptivity, which is uncommon in classical computational fields. There are myriad tools that capture the work across the many instances of the AI/ML lifecycle. The idea that any one tool could sufficiently capture the dynamic work is unrealistic. Take, for example, an experiment tracking tool like W&B or MLFlow; some form of experiment tracking is necessary in typical model training lifecycles. Such a tool requires some notion of a dataset. However, a tool focusing on experiment tracking is orthogonal to the needs of analyzing model performance at the data sample level, which is critical to understanding the failure modes of models. The way one does this depends on the type of data and the AI/ML task at hand. In other words, MLOps is inherently an intricate mosaic, as the capabilities and best practices of AI/ML work evolve.
-
My Favorite DevTools to Build AI/ML Applications!
MLflow is an open-source platform for managing the end-to-end machine learning lifecycle. It includes features for experiment tracking, model versioning, and deployment, enabling developers to track and compare experiments, package models into reproducible runs, and manage model deployment across multiple environments.
-
Exploring Open-Source Alternatives to Landing AI for Robust MLOps
Platforms such as MLflow monitor the development stages of machine learning models. In parallel, Data Version Control (DVC) brings version control system-like functions to the realm of data sets and models.
-
cascade alternatives - clearml and MLflow
3 projects | 1 Nov 2023
-
EL5: Difference between OpenLLM, LangChain, MLFlow
MLFlow - http://mlflow.org
- Explain me how websites like Dall-E, chatgpt, thispersondoesntexit process the user data so quickly
- [D] What licensed software do you use for machine learning experimentation tracking?
-
Exploring MLOps Tools and Frameworks: Enhancing Machine Learning Operations
MLflow:
-
Options for configuration of python libraries - Stack Overflow
In search for a tool that needs comparable configuration I looked into mlflow and found this. https://github.com/mlflow/mlflow/blob/master/mlflow/environment_variables.py There they define a class _EnvironmentVariable and create many objects out of it, for any variable they need. The get method of this class is in principle a decorated os.getenv. Maybe that is something I can take as orientation.
-
[D] Is there a tool to keep track of my ML experiments?
I have been using DVC and MLflow since then DVC had only data tracking and MLflow only model tracking. I can say both are awesome now and maybe the only factor I would like to mention is that IMO, MLflow is a bit harder to learn while DVC is just a git practically.
What are some alternatives?
civitai - A repository of models, textual inversions, and more
clearml - ClearML - Auto-Magical CI/CD to streamline your AI workload. Experiment Management, Data Management, Pipeline, Orchestration, Scheduling & Serving in one MLOps/LLMOps solution
transformers - 🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
Sacred - Sacred is a tool to help you configure, organize, log and reproduce experiments developed at IDSIA.
spaCy - 💫 Industrial-strength Natural Language Processing (NLP) in Python
zenml - ZenML 🙏: Build portable, production-ready MLOps pipelines. https://zenml.io.
mammography_metarepository - Meta-repository of screening mammography classifiers
guildai - Experiment tracking, ML developer tools
KoboldAI-Client
dvc - 🦉 ML Experiments and Data Management with Git
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
tensorflow - An Open Source Machine Learning Framework for Everyone