Comments (2)
Thanks for the feedback --
In order to create a model with the code in this repo, you can use code that looks something like:
from based.models.gpt import GPT2MixerConfig, GPTLMHeadModel
max_length = 2048
config=GPT2MixerConfig(
mixer={
"_target_": "based.models.mixers.slide_attention.SlidingAttention",
"window_size": 128 ,
"num_heads": 16
},
alt_mixer={
"_target_": "based.models.mixers.linear_attention.LinearAttention",
"l_max": 2048,
"feature_map": {
"_target_": "based.models.mixers.linear_attention.TaylorExp",
"input_dim": 16,
},
"feature_dim": 16,
"num_heads": 16,
"parallel_implementation": "linear"
},
alt_mixer_layers=[1,3,7,9],
n_positions=max_length,
)
model = GPTLMHeadModel(config=config)
We don't currently have plans to release a step-by-step training script. However, the training code in this repo https://github.com/HazyResearch/zoology, which we use for our synthetic language model exerimentsk, is a good bit simpler than the training code in this repo.
from based.
Thanks! That's helpful.
from based.
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