english : use typos
to fix comments and logs (#4354)
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6138963fb2
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9494d7c477
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
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temp->ny = longer_side;
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temp->size = 3 * longer_side * longer_side;
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temp->data = new uint8_t[temp->size]();
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uint8_t bc[3] = {122, 116, 104}; // bakground color in RGB from LLaVA
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uint8_t bc[3] = {122, 116, 104}; // background color in RGB from LLaVA
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// fill with background color
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for (size_t i = 0; i < temp->size; i++) {
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@ -51,7 +51,7 @@ def bytes_to_unicode():
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The reversible bpe codes work on unicode strings.
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This means you need a large # of unicode characters in your vocab if you want to avoid UNKs.
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When you're at something like a 10B token dataset you end up needing around 5K for decent coverage.
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This is a signficant percentage of your normal, say, 32K bpe vocab.
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This is a significant percentage of your normal, say, 32K bpe vocab.
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To avoid that, we want lookup tables between utf-8 bytes and unicode strings.
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And avoids mapping to whitespace/control characters the bpe code barfs on.
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"""
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@ -1,6 +1,6 @@
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# llama.cpp/examples/lookahead
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Demonstartion of lookahead decoding technique:
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Demonstration of lookahead decoding technique:
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https://lmsys.org/blog/2023-11-21-lookahead-decoding/
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@ -11227,7 +11227,7 @@ class binary_reader
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}
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if (is_ndarray) // ndarray dimensional vector can only contain integers, and can not embed another array
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{
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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));
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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));
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}
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std::vector<size_t> dim;
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if (JSON_HEDLEY_UNLIKELY(!get_ubjson_ndarray_size(dim)))
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@ -114,7 +114,7 @@ export async function* llama(prompt, params = {}, config = {}) {
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return content;
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}
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// Call llama, return an event target that you can subcribe to
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// Call llama, return an event target that you can subscribe to
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//
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// Example:
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//
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@ -238,7 +238,7 @@
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cache_prompt: true
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})
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/* START: Support for storing prompt templates and parameters in borwser LocalStorage */
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/* START: Support for storing prompt templates and parameters in browsers LocalStorage */
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const local_storage_storageKey = "llamacpp_server_local_storage";
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@ -282,7 +282,7 @@
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let importedTemplates = local_storage_getDataAsObject('user_templates')
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if (importedTemplates) {
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// saved templates were successfuly imported.
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// saved templates were successfully imported.
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console.log('Processing saved templates and updating default template')
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params.value = { ...params.value, image_data: [] };
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@ -303,7 +303,7 @@
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}
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function userTemplateResetToDefault() {
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console.log('Reseting themplate to default')
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console.log('Resetting template to default')
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selectedUserTemplate.value.name = 'default';
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selectedUserTemplate.value.data = savedUserTemplates.value['default'];
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}
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@ -1,6 +1,6 @@
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# llama.cpp/examples/speculative
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Demonstartion of speculative decoding and tree-based speculative decoding techniques
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Demonstration of speculative decoding and tree-based speculative decoding techniques
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More info:
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@ -428,7 +428,7 @@ int main(int argc, char ** argv) {
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++n_past_tgt;
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}
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// the first token is always proposed by the traget model before the speculation loop so we erase it here
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// the first token is always proposed by the target model before the speculation loop so we erase it here
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for (int s = 0; s < n_seq_dft; ++s) {
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if (!drafts[s].active) {
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continue;
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