Question 1

What is Dromedary?

Accepted Answer

Dromedary is an open-source self-aligned language model trained with minimal human supervision to be helpful, ethical, and reliable.

Question 2

What is the main goal of Dromedary?

Accepted Answer

Its goal is to build helpful, ethical, and reliable LLMs through principle-driven self-alignment from scratch.

Question 3

What are the key updates in Dromedary-2 (SFT)?

Accepted Answer

Dromedary-2 (SFT) simplifies SELF-ALIGN to two stages, mixing diverse user prompts (ShareGPT, Dolly-15k, OpenAssistant, OpenOrca) and an improved one-shot exemplar from FastChat that promotes a general–specific–general response style, dropping verbose cloning and few-shot inference prompts.

Question 4

Where is the training pipeline for Dromedary-2 (RLAIF)?

Accepted Answer

The RLAIF stage uses the SALMON pipeline (Self-ALignMent with principle-fOllowiNg reward models), available in the IBM/SALMON repository.

Question 5

How do I obtain the model weights for Dromedary?

Accepted Answer

Weights are released as delta weights (LoRA for Dromedary, QLoRA for Dromedary-2) to comply with the LLaMA licenses; download from Hugging Face and merge with the original LLaMA or LLaMA-2 base weights per the repo’s instructions.

Question 6

What synthetic data is available?

Accepted Answer

Synthetic instruction–response datasets for Dromedary-65B (final) and Dromedary-2-70B (SFT) are released on the Hugging Face Datasets Hub; instructions come from Self-Instruct with base LLaMA and responses from Dromedary with verbose prompts.

Question 7

How can I run inference or a chatbot demo?

Accepted Answer

The repository provides inference guides and a chatbot demo; for Dromedary-2, load QLoRA with PEFT-LoRA and bitsandbytes on a LLaMA-2-70B base using the specified system, user, and assistant prompts.

Question 8

What is the license for the repository?

Accepted Answer

The Dromedary repository is licensed under GPL-3.0; base model licenses (e.g., LLaMA/LLaMA-2) still apply to the required base weights.

Question 9

Which base models does Dromedary use?

Accepted Answer

Dromedary is trained on LLaMA base models, and Dromedary-2 uses LLaMA-2-70B for SFT/RLAIF; released weights are applied as deltas to these bases.

Question 10

Is there a paper I can read or cite?

Accepted Answer

Yes. The repository links to a NeurIPS 2023 Spotlight paper describing Dromedary and its self-alignment approach; see the repo for citation details.

Question 11

What is Dromedary?

Accepted Answer

Dromedary is an open-source self-aligned language model trained with minimal human supervision to be helpful, ethical, and reliable.

Question 12

What is the main goal of Dromedary?

Accepted Answer

Its goal is to build helpful, ethical, and reliable LLMs through principle-driven self-alignment from scratch.

Question 13

What are the key updates in Dromedary-2 (SFT)?

Accepted Answer

Dromedary-2 (SFT) simplifies SELF-ALIGN to two stages, mixing diverse user prompts (ShareGPT, Dolly-15k, OpenAssistant, OpenOrca) and an improved one-shot exemplar from FastChat that promotes a general–specific–general response style, dropping verbose cloning and few-shot inference prompts.

Question 14

Where is the training pipeline for Dromedary-2 (RLAIF)?

Accepted Answer

The RLAIF stage uses the SALMON pipeline (Self-ALignMent with principle-fOllowiNg reward models), available in the IBM/SALMON repository.

Question 15

How do I obtain the model weights for Dromedary?

Accepted Answer

Weights are released as delta weights (LoRA for Dromedary, QLoRA for Dromedary-2) to comply with the LLaMA licenses; download from Hugging Face and merge with the original LLaMA or LLaMA-2 base weights per the repo’s instructions.

Question 16

What synthetic data is available?

Accepted Answer

Synthetic instruction–response datasets for Dromedary-65B (final) and Dromedary-2-70B (SFT) are released on the Hugging Face Datasets Hub; instructions come from Self-Instruct with base LLaMA and responses from Dromedary with verbose prompts.

Question 17

How can I run inference or a chatbot demo?

Accepted Answer

The repository provides inference guides and a chatbot demo; for Dromedary-2, load QLoRA with PEFT-LoRA and bitsandbytes on a LLaMA-2-70B base using the specified system, user, and assistant prompts.

Question 18

What is the license for the repository?

Accepted Answer

The Dromedary repository is licensed under GPL-3.0; base model licenses (e.g., LLaMA/LLaMA-2) still apply to the required base weights.

Question 19

Which base models does Dromedary use?

Accepted Answer

Dromedary is trained on LLaMA base models, and Dromedary-2 uses LLaMA-2-70B for SFT/RLAIF; released weights are applied as deltas to these bases.

Question 20

Is there a paper I can read or cite?

Accepted Answer

Yes. The repository links to a NeurIPS 2023 Spotlight paper describing Dromedary and its self-alignment approach; see the repo for citation details.

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