The pros and cons of using different models
Each model has its pros and cons. Even if a model can generate fantastic results when you tell it to write some code in Python or it can write the most beautiful poems on command, it may still lack the ability to respond in the special way Auto-GPT needs it to.
Selecting a model with a certain strength in mind may result in improved performance.
The main advantages of using a local LLM are clear:
- Customization: Tailor the capabilities of Auto-GPT to your specific needs. For instance, a model trained on medical literature can make Auto-GPT adept at answering medical queries.
- Performance: Depending on the training and dataset, some models might outperform GPT in specific tasks.
- Cost efficiency: Running your local LLM reduces the cost of running it drastically. Using GPT-4 with lots of context and generally having many calls can quickly add up. Finding a way to break up the number of requests into smaller steps will make...
