Comments (3)
We believe how good is self extend highly depends on how good is the extended model within its original pretraining context window. This means if Qwen1.5's 32k context window is not well trained, SelfExtend may not work. Otherwise, it will work well. [Currently, we have no plan for a serious test considering the massive computational resource requirement: 32k 8x -> 256k, 4x -> 128k. We may do serious benchmarking for Qwen1.5 when we have enough resources.]
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Results on 128k length in str (around 70k as for qwen tokenizer). It seems work!
from longlm.
We believe how good is self extend highly depends on how good is the extended model within its original pretraining context window. This means if Qwen1.5's 32k context window is not well trained, SelfExtend may not work. Otherwise, it will work well. [Currently, we have no plan for a serious test considering the massive computational resource requirement: 32k 8x -> 256k, 4x -> 128k. We may do serious benchmarking for Qwen1.5 when we have enough resources.]
Ahhh, if I test it in the future work, i'll share it with you guys. Thanks for your reply~
from longlm.
Related Issues (20)
- Flash Attention implementation is coming
- Can it be implemented on qwen1.5? HOT 2
- Example for phi2? HOT 7
- llama_self_extend_patch_4_36 is not work HOT 7
- Example for gemma & use with Ollama HOT 5
- OOM on LongBench HOT 1
- FlashAttention does not work for Batch size > 1
- Something wrong in modify_method_of_instance function HOT 2
- Question | Has anyone tried this with GGUF models? HOT 2
- Long context
- Questions regarding group query/key positional index HOT 2
- Question about equation 4 and Table 5 caption in paper HOT 3
- llama3 is not working. HOT 1
- Expected all tensors to be on the same device, but found at least two devices, cuda:0 and cpu! when resuming training
- Passkey retrieval (needle in a haystack) HOT 2
- Run example.py Error: Failed to modify the attention method of LlamaForCausalLM HOT 2
- Differences with ReRoPE HOT 1
- 是否有示例代码支持对safetensors格式LLM启用SelfExtend HOT 5
- Cohere command r HOT 1
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