Exploring Chat Models: rwkv/raven 1.5B and fastchat-t5 3B
rwkv/raven 1.5B is a powerful model that can generate responses for conversations. You can find the model as ggml, which stands for "generalized generative model language." It offers an extensive corpus and has a context length of 4096, enabling it to handle long conversations effectively.
Another model to consider is fastchat-t5 3B. It's a chat model with a capacity of 3 billion tokens and is designed to hold engaging conversations. It utilizes the T5 architecture, which is known for its versatility in natural language processing tasks. The model has been fine-tuned on a wide range of conversational data, making it suitable for various chatbot applications.
One limitation of the fastchat-t5 model is its context length, which is relatively shorter compared to some other models. This means that it might struggle with conversations that have longer context or require more detailed responses. However, it compensates for this limitation by providing fast and efficient responses, making it an excellent choice for applications where quick interactions are preferred.
It's worth mentioning that there might be specific requirements for a simplified English text model with no uncommon words or other languages, but as of now, there isn't an open-source model available that precisely matches those criteria. However, the models mentioned above can still be valuable resources for developing conversational AI systems.