Fix convert script, warnings alpaca instructions, default params

README.md

@@ -193,15 +193,15 @@ First, download the `ggml` Alpaca model into the `./models` folder:
 ```
 # use one of these
 # TODO: add a script to simplify the download
-curl -o ggml2-alpaca-7b-q4.bin -C - https://gateway.estuary.tech/gw/ipfs/QmUp1UGeQFDqJKvtjbSYPBiZZKRjLp8shVP9hT8ZB9Ynv1
-curl -o ggml2-alpaca-7b-q4.bin -C - https://ipfs.io/ipfs/QmUp1UGeQFDqJKvtjbSYPBiZZKRjLp8shVP9hT8ZB9Ynv1
-curl -o ggml2-alpaca-7b-q4.bin -C - https://cloudflare-ipfs.com/ipfs/QmUp1UGeQFDqJKvtjbSYPBiZZKRjLp8shVP9hT8ZB9Ynv1
+curl -o ./models/ggml-alpaca-7b-q4.bin -C - https://gateway.estuary.tech/gw/ipfs/QmUp1UGeQFDqJKvtjbSYPBiZZKRjLp8shVP9hT8ZB9Ynv1
+curl -o ./models/ggml-alpaca-7b-q4.bin -C - https://ipfs.io/ipfs/QmUp1UGeQFDqJKvtjbSYPBiZZKRjLp8shVP9hT8ZB9Ynv1
+curl -o ./models/ggml-alpaca-7b-q4.bin -C - https://cloudflare-ipfs.com/ipfs/QmUp1UGeQFDqJKvtjbSYPBiZZKRjLp8shVP9hT8ZB9Ynv1
 ```
 
 Now run the `main` tool like this:
 
 ```
-./main -m ./models/ggml2-alpaca-7b-q4.bin --color -f ./prompts/alpaca.txt -ins
+./main -m ./models/ggml-alpaca-7b-q4.bin --color -f ./prompts/alpaca.txt -ins
 ```
 
 Sample run:
@@ -218,7 +218,7 @@ Sample run:
 There 26 letters in the English Alphabet
 > What is the most common way of transportation in Amsterdam?
 The majority (54%) are using public transit. This includes buses, trams and metros with over 100 lines throughout the city which make it very accessible for tourists to navigate around town as well as locals who commute by tram or metro on a daily basis
-> List 5 words that start with "ca".                                                                       
+> List 5 words that start with "ca".
 cadaver, cauliflower, cabbage (vegetable), catalpa (tree) and Cailleach.
 > 
 ```

alpaca.sh

@@ -3,4 +3,4 @@
 # Temporary script - will be removed in the future
 #
 
-./main -m ./models/ggml-alpaca-7b-q4.bin --color -f ./prompts/alpaca.txt -ins --top_k 10000 --temp 0.96 --repeat_penalty 1 -t 7
+./main -m ./models/ggml-alpaca-7b-q4.bin --color -f ./prompts/alpaca.txt -ins --top_k 10000 --temp 0.2 --repeat_penalty 1 -t 7

convert-pth-to-ggml.py

@@ -27,9 +27,9 @@ from sentencepiece import SentencePieceProcessor
 def parse_args():
 
     parser = argparse.ArgumentParser(description='Convert a LLaMA model checkpoint to a ggml compatible file')
-    parser.add_argument('dir_model', help='directory containing the model checkpoint')
-    parser.add_argument('ftype', type=int, choices=[0, 1], default=1, help='file type (0: float32, 1: float16)')
-    parser.add_argument('vocab_only', type=bool, default=False, help='only write vocab to file')
+    parser.add_argument('dir_model',  help='directory containing the model checkpoint')
+    parser.add_argument('ftype',      help='file type (0: float32, 1: float16)', type=int, choices=[0, 1], default=1)
+    parser.add_argument('vocab_only', help='only write vocab to file', type=int, default=0, nargs='?')
     return parser.parse_args()
 
 def get_n_parts(dim):
@@ -135,6 +135,8 @@ def main():
 
     hparams, tokenizer = load_hparams_and_tokenizer(dir_model)
 
+    print(args)
+
     # if only writing vocab to file
     if args.vocab_only:
 

main.cpp

@@ -165,12 +165,20 @@ bool llama_model_load(const std::string & fname, llama_model & model, llama_voca
     // load vocab
     {
         std::string word;
+        std::vector<char> tmp(64);
+
         for (int i = 0; i < model.hparams.n_vocab; i++) {
             uint32_t len;
             fin.read((char *) &len, sizeof(len));
 
             word.resize(len);
-            fin.read((char *) word.data(), len);
+            if (len > 0) {
+                tmp.resize(len);
+                fin.read(tmp.data(), len);
+                word.assign(tmp.data(), len);
+            } else {
+                word.clear();
+            }
 
             float score;
             fin.read((char *) &score, sizeof(score));
@@ -178,10 +186,6 @@ bool llama_model_load(const std::string & fname, llama_model & model, llama_voca
             vocab.token_to_id[word] = i;
             vocab.id_to_token[i] = word;
             vocab.score[i] = score;
-
-            //if (i < 30000) {
-            //    fprintf(stderr, "%s: vocab[%d] = '%s'\n", __func__, i, word.c_str());
-            //}
         }
     }
 
@@ -974,7 +978,7 @@ int main(int argc, char ** argv) {
         n_past += embd.size();
         embd.clear();
 
-        if (embd_inp.size() <= input_consumed) {
+        if ((int) embd_inp.size() <= input_consumed) {
             // out of user input, sample next token
             const float top_k = params.top_k;
             const float top_p = params.top_p;
@@ -1011,7 +1015,7 @@ int main(int argc, char ** argv) {
             --remaining_tokens;
         } else {
             // some user input remains from prompt or interaction, forward it to processing
-            while (embd_inp.size() > input_consumed) {
+            while ((int) embd_inp.size() > input_consumed) {
                 embd.push_back(embd_inp[input_consumed]);
                 last_n_tokens.erase(last_n_tokens.begin());
                 last_n_tokens.push_back(embd_inp[input_consumed]);
@@ -1036,7 +1040,7 @@ int main(int argc, char ** argv) {
 
         // in interactive mode, and not currently processing queued inputs;
         // check if we should prompt the user for more
-        if (params.interactive && embd_inp.size() <= input_consumed) {
+        if (params.interactive && (int) embd_inp.size() <= input_consumed) {
             // check for reverse prompt
             for (auto antiprompt_inp : antipromptv_inp) {
                 if (antiprompt_inp.size() && std::equal(antiprompt_inp.rbegin(), antiprompt_inp.rend(), last_n_tokens.rbegin())) {