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Tiny hackable CUDA language model implementation
oakinnagbe
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Gred_papa_dance
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* where is data (make data) how create new my own data, (questions for chat?) * how create a tokenizer (meybe separate) * how stop the code, how many memory need, how setup size of context etc. * how creating a LORA or learn with new data. * how quantize model?
In my opinion this is great idea but making a Ruby extension will be goot way to increase users using this code.
markusheimerl
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As the tokenizer adds substantial complexity, this implementation does not include any tokenziation logic and works on raw bytes. Feel free to add your own tokenzier with the help of the coding model of your choice.
You can stop the training using CTRL+C You can train on as little memory as you have. Simply reduce batch size and/or model dimensions in train.c You can change the context window size in train.c via the "seq_len" variable.
Regarding Ruby, LORA and quantization I'll have to refer you to the coding agent of your choice.
qqqqqlqq
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CUDA error in attention.c:91: out of memory
Command exited with non-zero status 1
1.38user 0.46system 0:00.75elapsed 246%CPU (0avgtext+0avgdata 226164maxresident)k
0inputs+0outputs (0major+25414minor)pagefaults 0swaps
make: ** [Makefile:34: run] Błąd 1
clang: warning: CUDA version 12.4 is only partially supported [-Wunknown-cuda-version]
(I have ubuntu and 8GB memory NVIDIA GeForce RTX 3050 876MiB / 8192MiB )
yobbo
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https://github.com/markusheimerl/gpt/blob/main/transformer/a...