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

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Richard Kiss 2023-12-12 01:53:36 -08:00 committed by GitHub
parent 6138963fb2
commit 9494d7c477
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17 changed files with 34 additions and 34 deletions

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@ -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++) {

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@ -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.
"""

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@ -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/

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@ -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)))

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@ -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:
//

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@ -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'];
}

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@ -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:

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@ -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;