Andrej Karpathy
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e808a67149
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bunch of plumbing of bias all around. measuring bias=False to be about 6% faster
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2023-01-27 20:41:17 +00:00 |
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Andrej Karpathy
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cc5444e194
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add the bias option to config, default it to True for now
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2023-01-27 20:29:45 +00:00 |
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Andrej Karpathy
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2bf07a3fbf
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rewrite model class so layernorm has an optional bias= parameter
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2023-01-27 20:17:32 +00:00 |
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Andrej Karpathy
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2892858ce7
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attempt a non-biased model, per few papers that cite this as working well
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2023-01-27 18:54:08 +00:00 |
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Andrej Karpathy
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23a0bfac20
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try bring back mingpt init
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2023-01-27 16:52:18 +00:00 |
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Andrej Karpathy
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89da79eee1
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add note of caution for the produced warning, investigate later
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2023-01-14 20:38:22 +00:00 |
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Andrej Karpathy
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91d02510ce
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fix bug... if topk > vocab_size, torch.topk will throw error
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2023-01-14 03:57:00 +00:00 |
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Andrej Karpathy
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43b37fd568
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reverse the order, making sure that the final layer init is preserved, and becomes the token embedding instead of the other way around. otherwise the loss can be all messed up from a bad init
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2023-01-14 02:16:10 +00:00 |
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Andrej Karpathy
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7c8288552b
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tie the weights of lm_head.weight and transformer.wte.weight, i.e. the last linear layer of decoder and the token embeddings.
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2023-01-14 01:00:55 +00:00 |
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Andrej Karpathy
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8f85b83347
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inference time mini-optimization low-hanging fruit ty @jxtps for raising: when we are running inference we can apply lm_head on only the very last token
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2023-01-12 06:02:50 +00:00 |
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Andrej Karpathy
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177d5f7dc5
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disabling torch.jit.script here for massive performance boost when using torch.compile, our default. see issue #11. thanks @vgoklani for flagging
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2023-01-02 23:05:01 +00:00 |
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Andrej Karpathy
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2febf4463c
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candidate changes to apis, have to think through more
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2023-01-01 01:29:48 +00:00 |
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ankandrew
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7f0e6d9a71
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Frozen GPTConfig
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2022-12-29 17:07:19 -03:00 |
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Andrej Karpathy
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fe8042867c
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first very bad commit
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2022-12-28 00:58:19 +00:00 |
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