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authorXiao-Yong Jin <jinxiaoyong@gmail.com>2023-07-15 06:34:16 -0400
committerGitHub <noreply@github.com>2023-07-15 13:34:16 +0300
commit6e7cca404748dd4b1a3affd0d1296e37f4ac0a6f (patch)
treedcbb7be0dbc8da79e0bf54d57a55b4b78b1dd461 /examples/main
parenta6803cab946c817fb7aaf2a40b317f5d3e373bd1 (diff)
llama : add custom RoPE (#2054)
* Implement customizable RoPE The original RoPE has pre-defined parameters theta_i = 10000^(āˆ’2(iāˆ’1)/d), for i in [1, 2, ..., d/2] Our customizable RoPE, ggml_rope_custom_inplace, uses theta_i = scale * base^(āˆ’2(iāˆ’1)/d), for i in [1, 2, ..., d/2] with the default matches the original scale = 1.0 base = 10000 The new command line arguments --rope-freq-base --rope-freq-scale set the two new RoPE parameter. Recent researches show changing these two parameters extends the context limit with minimal loss. 1. Extending Context to 8K kaiokendev https://kaiokendev.github.io/til#extending-context-to-8k 2. Extending Context Window of Large Language Models via Positional Interpolation Shouyuan Chen, Sherman Wong, Liangjian Chen, Yuandong Tian https://arxiv.org/abs/2306.15595 3. NTK-Aware Scaled RoPE allows LLaMA models to have extended (8k+) context size without any fine-tuning and minimal perplexity degradation. https://www.reddit.com/user/bloc97 https://www.reddit.com/r/LocalLLaMA/comments/14lz7j5/ntkaware_scaled_rope_allows_llama_models_to_have/ For the bold, try adding the following command line parameters to your favorite model: -c 16384 --rope-freq-base 80000 --rope-freq-scale 0.5 * ggml-metal: fix custom rope * common: fix argument names in help * llama: increase MEM_REQ_EVAL for MODEL_3B It avoids crashing for quantized weights on CPU. Better ways to calculate the required buffer size would be better. * llama: make MEM_REQ_EVAL depend on n_ctx * server: use proper Content-Type in curl examples Without the header Content-Type: application/json, curl will POST with Content-Type: application/x-www-form-urlencoded Though our simple server doesn't care, the httplib.h used has a limit with CPPHTTPLIB_FORM_URL_ENCODED_PAYLOAD_MAX_LENGTH 8192 With Content-Type: application/json, we can send large json data. * style : minor fixes, mostly indentations * ggml : fix asserts --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
Diffstat (limited to 'examples/main')
-rw-r--r--examples/main/main.cpp12
1 files changed, 10 insertions, 2 deletions
diff --git a/examples/main/main.cpp b/examples/main/main.cpp
index 2248c24..bcbcf12 100644
--- a/examples/main/main.cpp
+++ b/examples/main/main.cpp
@@ -84,9 +84,17 @@ int main(int argc, char ** argv) {
return 0;
}
+ if (params.rope_freq_base != 10000.0) {
+ fprintf(stderr, "%s: warning: changing RoPE frequency base to %g (default 10000.0)\n", __func__, params.rope_freq_base);
+ }
+
+ if (params.rope_freq_scale != 1.0) {
+ fprintf(stderr, "%s: warning: scaling RoPE frequency by %g (default 1.0)\n", __func__, params.rope_freq_scale);
+ }
+
if (params.n_ctx > 2048) {
- fprintf(stderr, "%s: warning: model might not support context sizes greater than 2048 tokens (%d specified);"
- "expect poor results\n", __func__, params.n_ctx);
+ fprintf(stderr, "%s: warning: base model only supports context sizes no greater than 2048 tokens (%d specified);"
+ " you are on your own\n", __func__, params.n_ctx);
} else if (params.n_ctx < 8) {
fprintf(stderr, "%s: warning: minimum context size is 8, using minimum size.\n", __func__);
params.n_ctx = 8;