dolly
by Community
Databricks’ Dolly, a large language model trained on the Databricks Machine Learning Platform
OSS
dolly
Added 1 June 2026
Overview
Dolly is a large language model trained on the Databricks Machine Learning Platform. It is designed for instruction following and fine-tuning on custom datasets. The model is open source and available under a community license.
Best for
Best for
Developers and researchers who want to fine-tune a mid-sized open-source LLM on Databricks infrastructure.
Use cases
- Fine-tuning a language model on domain-specific instructions
- Building a conversational agent for customer support
- Generating code or documentation from natural language prompts
Notes
Dolly is a large language model trained on the Databricks Machine Learning Platform. It is designed for instruction following and fine-tuning on custom datasets. The model is open source and available under a community license.
10,790 stars on GitHub. Last updated 2023-06-30. Licensed Apache-2.0.
Use cases
- Fine-tuning a language model on domain-specific instructions
- Building a conversational agent for customer support
- Generating code or documentation from natural language prompts
Pros
- Open source with permissive community license
- Trained on a robust enterprise ML platform
- Good foundation for custom instruction-following tasks
Cons
- Requires substantial GPU memory for inference and training
- Not as capable as larger proprietary models for complex reasoning
- Limited pre-training data scope compared to frontier models
Indexed from awesome-llmops and enriched against its public facts.
Pros
- Open source with permissive community license
- Trained on a robust enterprise ML platform
- Good foundation for custom instruction-following tasks
Cons
- Requires substantial GPU memory for inference and training
- Not as capable as larger proprietary models for complex reasoning
- Limited pre-training data scope compared to frontier models
Pairs with
Other entries in the index that connect to this one. Click through to see the chain.