Starling Models by Nexusflow
About
The Starling family of Large Language Models (LLMs) stems from the innovative Berkeley-Nest AI research group. Among its models, Starling-LM-7B-alpha stands out as a 7-billion parameter language model specifically fine-tuned using Reinforcement Learning from AI Feedback (RLAIF). This fine-tuning process harnessed the extensive Nectar dataset, comprising GPT-4-ranked chat prompts and responses. Starling-LM-7B-alpha focuses on enhancing its helpfulness and maintaining a non-harmful approach, evolving from the Openchat 3.5 model. The project also introduced the Starling-RM-7B-alpha reward model, pivotal for RLAIF processes. To foster advancements in RLHF mechanisms and AI safety, the dataset, reward model, and language model are openly accessible. Additionally, a more refined iteration, Starling-LM-7B-beta, has been made available for further research and development.
Current Variants
Use-when guidance is derived from seed capabilities, context, release, and replacement fields.
Use when the workload needs 8k context and 7B parameters.
| Model | Use when | Released | Signals | Status |
|---|---|---|---|---|
| Starling LM 7B Beta | Use when the workload needs 8k context and 7B parameters. | 2024-02 | 8k context7B parameters | Current |
Release Timeline
1 release groupSpecifications(1 models)
| Model | Released | Context | Parameters |
|---|---|---|---|
| Starling LM 7B Beta | 2024-02 | 8k | 7B |
Frequently Asked Questions
- What is Starling used for?
- Starling is used for coding. The family description and listed model capabilities point to those workloads as the best fit.
- How does Starling compare to NexusRaven?
- Starling by Nexusflow is strongest where you need coding, while NexusRaven by Nexusflow is the closest related family to check for structured outputs. Starling has 1 listed variant and reaches up to 8k context, while NexusRaven reaches up to 100k context, so compare the specs and pricing tables before choosing a production model.
- Which Starling model should I use?
- If price is the main constraint, use the pricing table first because Starling does not have complete provider pricing in the local data. For the most capable/latest local choice, evaluate Starling LM 7B Beta with 8k context.
