🚀 Dockerize llamacpp (#132)

* feat: dockerize llamacpp

* feat: split build & runtime stages

* split dockerfile into main & tools

* add quantize into tool docker image

* Update .devops/tools.sh

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

* add docker action pipeline

* change CI to publish at github docker registry

* fix name runs-on macOS-latest is macos-latest (lowercase)

* include docker versioned images

* fix github action docker

* fix docker.yml

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

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

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))