Top 3 Self-Hosted LLMs Considerations

1. Hugging Face Transformers:
   • Pros: This is a library that offers a variety of pre-trained models, including some that are smaller and more manageable for a home desktop environment.
   • Cons: Requires understanding of Python programming and setting up an environment for running these models.
   • Multi-Language Support: Many models support multiple languages, including Spanish, English, and Russian.
2. EleutherAI's GPT-Neo/GPT-J:
   • Pros: Open-source alternatives to GPT-3. GPT-Neo and GPT-J are designed to be more accessible and can be run on personal hardware.
   • Cons: They still require substantial computational resources. Setting up and maintaining the model may be challenging.
   • Multi-Language Support: Primarily English, but some capabilities for other languages might be present.
3. TensorFlow or PyTorch based small-scale models:
   • Pros: Easier to deploy on a home desktop with limited resources. These frameworks offer a variety of models that can be fine-tuned or used directly.
   • Cons: Requires a good understanding of machine learning frameworks and model management.
   • Multi-Language Support: Depends on the specific model chosen.