feat: include all-in-one command tool & update readme.md

.devops/tools.sh

@@ -1,4 +1,5 @@
 #!/bin/bash
+set -e
 
 # Read the first argument into a variable
 arg1="$1"
@@ -12,13 +13,34 @@ arg2="$@"
 if [[ $arg1 == '--convert' || $arg1 == '-c' ]]; then
     python3 ./convert-pth-to-ggml.py $arg2
 elif [[ $arg1 == '--quantize' || $arg1 == '-q' ]]; then
-    /app/quantize $arg2
+    ./quantize $arg2
 elif [[ $arg1 == '--run' || $arg1 == '-r' ]]; then
-    /app/main $arg2
+    ./main $arg2
+elif [[ $arg1 == '--download' || $arg1 == '-d' ]]; then
+    python3 ./download-pth.py $arg2
+elif [[ $arg1 == '--all-in-one' || $arg1 == '-a' ]]; then
+    echo "Downloading model..."
+    python3 ./download-pth.py "$1" "$2"
+    echo "Converting PTH to GGML..."
+    for i in `ls $1/$2/ggml-model-f16.bin*`; do
+        if [ -f "${i/f16/q4_0}" ]; then
+            echo "Skip model quantization, it already exists: ${i/f16/q4_0}"
+        else
+            echo "Converting PTH to GGML: $i into ${i/f16/q4_0}..."
+            ./quantize "$i" "${i/f16/q4_0}" 2
+        fi
+    done
 else
     echo "Unknown command: $arg1"
     echo "Available commands: "
-    echo "  --run (-r)"
-    echo "  --convert (-c)"
-    echo "  --quantize (-q)"
+    echo "  --run (-r): Run a model previously converted into ggml"
+    echo "              ex: -m /models/7B/ggml-model-q4_0.bin -p \"Building a website can be done in 10 simple steps:\" -t 8 -n 512"
+    echo "  --convert (-c): Convert a llama model into ggml"
+    echo "              ex: \"/models/7B/\" 1"
+    echo "  --quantize (-q): Optimize with quantization process ggml"
+    echo "              ex: \"/models/7B/ggml-model-f16.bin\" \"/models/7B/ggml-model-q4_0.bin\" 2"
+    echo "  --download (-d): Download original llama model from CDN: https://agi.gpt4.org/llama/"
+    echo "              ex: \"/models/\" 7B"
+    echo "  --all-in-one (-a): Execute --download, --convert & --quantize"
+    echo "              ex: \"/models/\" 7B"
 fi

README.md

@@ -32,6 +32,7 @@ Supported platforms:
 - [X] Mac OS
 - [X] Linux
 - [X] Windows (via CMake)
+- [X] Docker
 
 ---
 
@@ -194,6 +195,37 @@ Finally, copy the `llama` binary and the model files to your device storage. Her
 
 https://user-images.githubusercontent.com/271616/225014776-1d567049-ad71-4ef2-b050-55b0b3b9274c.mp4
 
+### Docker
+
+#### Prerequisites
+* Docker must be installed and running on your system.
+* Create a folder to store big models & intermediate files (in ex. im using /llama/models)
+
+#### Images
+We have two Docker images available for this project:
+
+1. `ghcr.io/ggerganov/llama.cpp:full`: This image includes both the main executable file and the tools to convert LLaMA models into ggml and convert into 4-bit quantization.
+2. `ghcr.io/ggerganov/llama.cpp:light`: This image only includes the main executable file.
+
+#### Usage
+
+The easiest way to download the models, convert them to ggml and optimize them is with the --all-in-one command which includes the full docker image.
+
+ ```bash
+docker run -v /llama/models:/models ghcr.io/ggerganov/llama.cpp:full --all-in-one "/models/" 7B
+```
+
+On complete, you are ready to play!
+
+```bash
+docker run -v /llama/models:/models ghcr.io/ggerganov/llama.cpp:full --run -m /models/7B/ggml-model-q4_0.bin -p "Building a website can be done in 10 simple steps:" -t 8 -n 512
+```
+
+or with light image:
+
+```bash
+docker run -v /llama/models:/models ghcr.io/ggerganov/llama.cpp:light -m /models/7B/ggml-model-q4_0.bin -p "Building a website can be done in 10 simple steps:" -t 8 -n 512
+```
 
 ## Limitations
 

convert-pth-to-ggml.py

@@ -16,7 +16,7 @@
 # At the start of the ggml file we write the model parameters
 # and vocabulary.
 #
-
+import os
 import sys
 import json
 import struct
@@ -64,6 +64,10 @@ if len(sys.argv) > 2:
         sys.exit(1)
     fname_out = sys.argv[1] + "/ggml-model-" + ftype_str[ftype] + ".bin"
 
+if os.path.exists(fname_out):
+    print(f"Skip conversion, it already exists: {fname_out}")
+    sys.exit(0)
+
 with open(fname_hparams, "r") as f:
     hparams = json.load(f)
 

download-pth.py

@@ -0,0 +1,66 @@
+import os
+import sys
+from tqdm import tqdm
+import requests
+
+if len(sys.argv) < 3:
+    print("Usage: download-pth.py dir-model model-type\n")
+    print("  model-type: Available models 7B, 13B, 30B or 65B")
+    sys.exit(1)
+
+modelsDir = sys.argv[1]
+model = sys.argv[2]
+
+num = {
+    "7B": 1,
+    "13B": 2,
+    "30B": 4,
+    "65B": 8,
+}
+
+if model not in num:
+    print(f"Error: model {model} is not valid, provide 7B, 13B, 30B or 65B")
+    sys.exit(1)
+
+print(f"Downloading model {model}")
+
+files = ["checklist.chk", "params.json"]
+
+for i in range(num[model]):
+    files.append(f"consolidated.0{i}.pth")
+
+resolved_path = os.path.abspath(os.path.join(modelsDir, model))
+os.makedirs(resolved_path, exist_ok=True)
+
+for file in files:
+    dest_path = os.path.join(resolved_path, file)
+    
+    if os.path.exists(dest_path):
+        print(f"Skip file download, it already exists: {file}")
+        continue
+
+    url = f"https://agi.gpt4.org/llama/LLaMA/{model}/{file}"
+    response = requests.get(url, stream=True)
+    with open(dest_path, 'wb') as f:
+        with tqdm(unit='B', unit_scale=True, miniters=1, desc=file) as t:
+            for chunk in response.iter_content(chunk_size=1024):
+                if chunk:
+                    f.write(chunk)
+                    t.update(len(chunk))
+
+files2 = ["tokenizer_checklist.chk", "tokenizer.model"]
+for file in files2:
+    dest_path = os.path.join(modelsDir, file)
+    
+    if os.path.exists(dest_path):
+        print(f"Skip file download, it already exists: {file}")
+        continue
+    
+    url = f"https://agi.gpt4.org/llama/LLaMA/{file}"
+    response = requests.get(url, stream=True)
+    with open(dest_path, 'wb') as f:
+        with tqdm(unit='B', unit_scale=True, miniters=1, desc=file) as t:
+            for chunk in response.iter_content(chunk_size=1024):
+                if chunk:
+                    f.write(chunk)
+                    t.update(len(chunk))