english : use `typos` to fix comments and logs (#4354)

8 files changed, 10 insertions, 10 deletions

diff --git a/examples/llava/clip.cpp b/examples/llava/clip.cpp
index fc0656c2..4bb7b93b 100644
--- a/examples/llava/clip.cpp
+++ b/examples/llava/clip.cpp
@@ -739,7 +739,7 @@ bool clip_image_preprocess(const clip_ctx * ctx, const clip_image_u8 * img, clip
         temp->ny = longer_side;
         temp->size = 3 * longer_side * longer_side;
         temp->data = new uint8_t[temp->size]();
-        uint8_t bc[3] = {122, 116, 104}; // bakground color in RGB from LLaVA
+        uint8_t bc[3] = {122, 116, 104}; // background color in RGB from LLaVA
 
         // fill with background color
         for (size_t i = 0; i < temp->size; i++) {
diff --git a/examples/llava/convert-image-encoder-to-gguf.py b/examples/llava/convert-image-encoder-to-gguf.py
index 729aaef8..03688e0e 100644
--- a/examples/llava/convert-image-encoder-to-gguf.py
+++ b/examples/llava/convert-image-encoder-to-gguf.py
@@ -51,7 +51,7 @@ def bytes_to_unicode():
     The reversible bpe codes work on unicode strings.
     This means you need a large # of unicode characters in your vocab if you want to avoid UNKs.
     When you're at something like a 10B token dataset you end up needing around 5K for decent coverage.
-    This is a signficant percentage of your normal, say, 32K bpe vocab.
+    This is a significant percentage of your normal, say, 32K bpe vocab.
     To avoid that, we want lookup tables between utf-8 bytes and unicode strings.
     And avoids mapping to whitespace/control characters the bpe code barfs on.
     """
diff --git a/examples/lookahead/README.md b/examples/lookahead/README.md
index 252a6689..a69a471b 100644
--- a/examples/lookahead/README.md
+++ b/examples/lookahead/README.md
@@ -1,6 +1,6 @@
 # llama.cpp/examples/lookahead
 
-Demonstartion of lookahead decoding technique:
+Demonstration of lookahead decoding technique:
 
 https://lmsys.org/blog/2023-11-21-lookahead-decoding/
 
diff --git a/examples/server/json.hpp b/examples/server/json.hpp
index 4d1a37ad..ea945f34 100644
--- a/examples/server/json.hpp
+++ b/examples/server/json.hpp
@@ -11227,7 +11227,7 @@ class binary_reader
                 }
                 if (is_ndarray) // ndarray dimensional vector can only contain integers, and can not embed another array
                 {
-                    return sax->parse_error(chars_read, get_token_string(), parse_error::create(113, chars_read, exception_message(input_format, "ndarray dimentional vector is not allowed", "size"), nullptr));
+                    return sax->parse_error(chars_read, get_token_string(), parse_error::create(113, chars_read, exception_message(input_format, "ndarray dimensional vector is not allowed", "size"), nullptr));
                 }
                 std::vector<size_t> dim;
                 if (JSON_HEDLEY_UNLIKELY(!get_ubjson_ndarray_size(dim)))
diff --git a/examples/server/public/completion.js b/examples/server/public/completion.js
index b9c44250..c281f0fb 100644
--- a/examples/server/public/completion.js
+++ b/examples/server/public/completion.js
@@ -114,7 +114,7 @@ export async function* llama(prompt, params = {}, config = {}) {
   return content;
 }
 
-// Call llama, return an event target that you can subcribe to
+// Call llama, return an event target that you can subscribe to
 //
 // Example:
 //
diff --git a/examples/server/public/index.html b/examples/server/public/index.html
index 175c5247..18a6ccf0 100644
--- a/examples/server/public/index.html
+++ b/examples/server/public/index.html
@@ -238,7 +238,7 @@
       cache_prompt: true
     })
 
-    /* START: Support for storing prompt templates and parameters in borwser LocalStorage */
+    /* START: Support for storing prompt templates and parameters in browsers LocalStorage */
 
     const local_storage_storageKey = "llamacpp_server_local_storage";
 
@@ -282,7 +282,7 @@
     let importedTemplates = local_storage_getDataAsObject('user_templates')
 
     if (importedTemplates) {
-      // saved templates were successfuly imported.
+      // saved templates were successfully imported.
 
       console.log('Processing saved templates and updating default template')
       params.value = { ...params.value, image_data: [] };
@@ -303,7 +303,7 @@
     }
 
     function userTemplateResetToDefault() {
-      console.log('Reseting themplate to default')
+      console.log('Resetting template to default')
       selectedUserTemplate.value.name = 'default';
       selectedUserTemplate.value.data = savedUserTemplates.value['default'];
     }
diff --git a/examples/speculative/README.md b/examples/speculative/README.md
index d88fd379..814efa59 100644
--- a/examples/speculative/README.md
+++ b/examples/speculative/README.md
@@ -1,6 +1,6 @@
 # llama.cpp/examples/speculative
 
-Demonstartion of speculative decoding and tree-based speculative decoding techniques
+Demonstration of speculative decoding and tree-based speculative decoding techniques
 
 More info:
 
diff --git a/examples/speculative/speculative.cpp b/examples/speculative/speculative.cpp
index dca3f84a..20f1fb5b 100644
--- a/examples/speculative/speculative.cpp
+++ b/examples/speculative/speculative.cpp
@@ -428,7 +428,7 @@ int main(int argc, char ** argv) {
             ++n_past_tgt;
         }
 
-        // the first token is always proposed by the traget model before the speculation loop so we erase it here
+        // the first token is always proposed by the target model before the speculation loop so we erase it here
         for (int s = 0; s < n_seq_dft; ++s) {
             if (!drafts[s].active) {
                 continue;