Hello!
By popular demand I am planning a fine-tune of https://huggingface.co/dreamgen/opus-v0-7b on top of Yi-34B and wonder whether to use the 200K as the base.
The regular Yi-34B seems slightly better than Yi-34B-200K on standard benchmarks, but I wonder how it “feels” and whether the loss of performance on short context is worth it, given that the regular version can be used up to 32K tokens.
Did anyone try an analysis of these 2 models on various sequence lengths (<4K, <8K, <16K, etc.)?
In most scenarios, models with extended context are optimized for long sequences. If the sequence is not very long, it is often recommended to use a regular model