starchat-alpha
Maintainer: HuggingFaceH4
229
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| Property | Value |
|---|---|
| Run this model | Run on HuggingFace |
| API spec | View on HuggingFace |
| Github link | No Github link provided |
| Paper link | No paper link provided |
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Model overview
starchat-alpha is a language model developed by HuggingFaceH4 that is fine-tuned from the bigcode/starcoderbase model to act as a helpful coding assistant. It is the first in a series of "StarChat" models, and as an alpha release, is intended only for educational or research purposes. The model has not been aligned to human preferences using techniques like Reinforcement Learning from Human Feedback (RLHF), so it may generate problematic content, especially if prompted to do so.
In contrast, the starchat2-15b-v0.1 model is a later version in the series that has been fine-tuned using Supervised Fine-Tuning (SFT) and Debate-Preference Optimization (DPO) on a mix of synthetic datasets. It achieves stronger performance on chat and programming benchmarks compared to starchat-alpha.
The Starling-LM-7B-alpha and Starling-LM-7B-beta models are also fine-tuned language models, but they use Reinforcement Learning from AI Feedback (RLAIF) and Preference Learning (PPO) techniques to improve helpfulness and safety.
Model inputs and outputs
Inputs
- Natural language prompts: The model can accept natural language prompts, such as questions or instructions, that are related to programming tasks.
Outputs
- Code snippets: The model can generate code snippets in response to programming-related prompts.
- Natural language responses: The model can also provide natural language responses to explain or clarify its code outputs.
Capabilities
starchat-alpha can generate code snippets in a variety of programming languages based on the provided prompts. It demonstrates strong capabilities in areas like syntax generation, algorithm implementation, and software engineering best practices. However, the model's outputs may contain bugs, security vulnerabilities, or other issues, as it has not been thoroughly aligned to ensure safety and reliability.
What can I use it for?
starchat-alpha can be used for educational and research purposes to explore the capabilities of open-source language models in the programming domain. Developers and researchers can experiment with the model to gain insights into its strengths and limitations, and potentially use it as a starting point for further fine-tuning or research into more robust and reliable coding assistants.
Things to try
One interesting aspect of starchat-alpha is its tendency to generate false URLs. Users should carefully inspect any URLs produced by the model before clicking on them, as they may lead to unintended or potentially harmful destinations. Experimenting with prompts that test the model's URL generation capabilities could yield valuable insights into its limitations and potential risks.
Additionally, users could try prompting the model to generate code for specific programming tasks or challenges, and then evaluate the quality, correctness, and security of the resulting code snippets. This could help identify areas where the model performs well, as well as areas where further refinement or alignment is needed.
This summary was produced with help from an AI and may contain inaccuracies - check out the links to read the original source documents!
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