llama : grouped-query attention + LLaMAv2 70B support (#2276)
* CUDA: GQA implementation * llama : support for GQA and LLaMAv2 70B ggml-ci * py : fix hparams parsing (if-else blocks) ggml-ci * py : oh boy .. ggml-ci * help : fix gqa value for 70B ggml-ci --------- Co-authored-by: JohannesGaessler <johannesg@5d6.de>
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7 changed files with 215 additions and 108 deletions
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@ -27,6 +27,7 @@ struct gpt_params {
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int32_t n_predict = -1; // new tokens to predict
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int32_t n_ctx = 512; // context size
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int32_t n_batch = 512; // batch size for prompt processing (must be >=32 to use BLAS)
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int32_t n_gqa = 1; // grouped-query attention factor (TODO: move to hparams)
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int32_t n_keep = 0; // number of tokens to keep from initial prompt
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int32_t n_chunks = -1; // max number of chunks to process (-1 = unlimited)
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int32_t n_gpu_layers = 0; // number of layers to store in VRAM
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@ -47,7 +48,7 @@ struct gpt_params {
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int32_t repeat_last_n = 64; // last n tokens to penalize (0 = disable penalty, -1 = context size)
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float frequency_penalty = 0.00f; // 0.0 = disabled
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float presence_penalty = 0.00f; // 0.0 = disabled
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int mirostat = 0; // 0 = disabled, 1 = mirostat, 2 = mirostat 2.0
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int32_t mirostat = 0; // 0 = disabled, 1 = mirostat, 2 = mirostat 2.0
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float mirostat_tau = 5.00f; // target entropy
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float mirostat_eta = 0.10f; // learning rate
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