RWKV is an RNN with transformer-level LLM performance. It can be directly trained like a GPT (parallelizable). So it's combining the best of RNN and transformer - great performance, fast inference, saves VRAM, fast training, "infinite" ctx_len, and free sentence embedding.
完全采用垂直领域的样本,结果忘记通用领域的所有技能。 不确定在这个模型中如何解决这个问题?
Forget all the skills in the general domain with my samples. How to fix this in this model?