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Build LLM projects with DagsHub 
Efficiently log prompts and experiments, ensuring transparency and mitigating biases or hallucinations in your LLM. Track and evaluate data for accurate model assessment, while labeling data for RLHF.
Your source of truth for LLM customization

RLHF Annotations

Rank and categorize your LLM generations so that you can perform reinforcement learning from human feedback

  • Integrated data annotation
  • Visual ranking templates

LLM Evaluation

Curate datasets of prompts and generations to better evaluate your model.
Reduce the chances of your model being biased/hallucinating with unlikely results

  • Data curation
  • Datasets versioning

Prompt Tracking

Track your prompts and LLM responses, visualize and compare results of exprimental submissions

  • Prompt logging
  • Manage customized LLM models
Zero DevOps!

Avoid the MLOps “tedious work” by using DagsHub’s capabilities without relying on your DevOps.

We do the heavy lifting for you

We will host the servers for data versioning, labeling, and experiment tracking and set up a central repository, so you can just work on ML

No need to be familiar with different tools

You will use a bunch of great tools, but work with only one interface, much more convenient

Get started working faster

Since we’re doing all the setup,
your step 1 is machine learning work!

Don’t just take our word for it..
Transform your ML development with DagsHub – try it now
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MLOps

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DVC

Getting Started With DVC

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Photos by Milad Fakurian on Unsplash

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See how leading data scientists manage their data and quickly take models to production.

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