Merge f5d35391db into bc1fca39f3

nanochat/dataset.py

@@ -11,6 +11,7 @@ import os
 import argparse
 import time
 import requests
+import pyarrow.fs as fs
 import pyarrow.parquet as pq
 from multiprocessing import Pool
 
@@ -20,7 +21,7 @@ from nanochat.common import get_base_dir
 # The specifics of the current pretraining dataset
 
 # The URL on the internet where the data is hosted and downloaded from on demand
-BASE_URL = "https://huggingface.co/datasets/karpathy/fineweb-edu-100b-shuffle/resolve/main"
+BASE_URI = "hf://datasets/karpathy/fineweb-edu-100b-shuffle"
 MAX_SHARD = 1822 # the last datashard is shard_01822.parquet
 index_to_filename = lambda index: f"shard_{index:05d}.parquet" # format of the filenames
 base_dir = get_base_dir()
@@ -68,45 +69,17 @@ def download_single_file(index):
         return True
 
     # Construct the remote URL for this file
-    url = f"{BASE_URL}/{filename}"
+    uri = f"{BASE_URI}/{filename}"
     print(f"Downloading {filename}...")
-
-    # Download with retries
-    max_attempts = 5
-    for attempt in range(1, max_attempts + 1):
-        try:
-            response = requests.get(url, stream=True, timeout=30)
-            response.raise_for_status()
-            # Write to temporary file first
-            temp_path = filepath + f".tmp"
-            with open(temp_path, 'wb') as f:
-                for chunk in response.iter_content(chunk_size=1024 * 1024):  # 1MB chunks
-                    if chunk:
-                        f.write(chunk)
-            # Move temp file to final location
-            os.rename(temp_path, filepath)
-            print(f"Successfully downloaded {filename}")
-            return True
-
-        except (requests.RequestException, IOError) as e:
-            print(f"Attempt {attempt}/{max_attempts} failed for {filename}: {e}")
-            # Clean up any partial files
-            for path in [filepath + f".tmp", filepath]:
-                if os.path.exists(path):
-                    try:
-                        os.remove(path)
-                    except:
-                        pass
-            # Try a few times with exponential backoff: 2^attempt seconds
-            if attempt < max_attempts:
-                wait_time = 2 ** attempt
-                print(f"Waiting {wait_time} seconds before retry...")
-                time.sleep(wait_time)
-            else:
-                print(f"Failed to download {filename} after {max_attempts} attempts")
-                return False
-
-    return False
+    try:
+        # pyarrow.fs uses huggingface_hub with builtin exponential backoff
+        fs.copy_files(uri, filepath)
+    except (requests.RequestException, IOError) as e:
+        print(f"Failed to download {filename}: {e}")
+        return False
+    else:
+        print(f"Successfully downloaded {filename}")
+        return True
 
 
 if __name__ == "__main__":

nanochat/gpt.py

@@ -8,7 +8,7 @@ Notable features:
 - norm after token embedding
 - no learnable params in rmsnorm
 - no bias in linear layers
-- Multi-Query Attention (MQA) support for more efficient inference
+- Group-Query Attention (GQA) support for more efficient inference
 """
 
 import math
@@ -29,7 +29,7 @@ class GPTConfig:
     vocab_size: int = 50304
     n_layer: int = 12
     n_head: int = 6 # number of query heads
-    n_kv_head: int = 6 # number of key/value heads (MQA)
+    n_kv_head: int = 6 # number of key/value heads (GQA)
     n_embd: int = 768
 
 

pyproject.toml

@@ -9,6 +9,7 @@ dependencies = [
     "fastapi>=0.117.1",
     "files-to-prompt>=0.6",
     "psutil>=7.1.0",
+    "pyarrow>=21.0.0",
     "regex>=2025.9.1",
     "setuptools>=80.9.0",
     "tiktoken>=0.11.0",