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data_19b.bin

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+version https://git-lfs.github.com/spec/v1
+oid sha256:5b88ffa322bcbf78c8b143b73e8305294a9cd121dc4f5e06569ae16acc1fb562
+size 40135044184

test.py

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+import os
+import numpy as np
+import random
+from transformers import GPT2Tokenizer
+
+# --- Settings ---
+BIN_PATH = "data_19b.bin"
+NUM_SAMPLES = 10
+SAMPLE_LEN = 200 # Number of tokens to decode per sample
+
+def main():
+    if not os.path.exists(BIN_PATH):
+        print(f"Error: {BIN_PATH} not found.")
+        return
+
+    # 1. Load the tokenizer
+    print("Loading GPT-2 Tokenizer...")
+    tokenizer = GPT2Tokenizer.from_pretrained("EleutherAI/gpt-neox-20b")
+
+    # 2. Map the data (instantly points to the 40GB file)
+    data = np.memmap(BIN_PATH, dtype=np.uint16, mode='r')
+    total_tokens = len(data)
+    print(f"File loaded. Total tokens: {total_tokens:,}")
+
+    # 3. Pick random spots and decode
+    print(f"\n--- Decoding {NUM_SAMPLES} Random Samples ---\n")
+    
+    for i in range(NUM_SAMPLES):
+        # Pick a random starting index
+        start_idx = random.randint(0, total_tokens - SAMPLE_LEN)
+        end_idx = start_idx + SAMPLE_LEN
+        
+        # Pull the uint16 tokens and convert to standard Python list
+        token_ids = data[start_idx:end_idx].tolist()
+        
+        # Decode to text
+        decoded_text = tokenizer.decode(token_ids, skip_special_tokens=True)
+        
+        print(f"Sample {i+1} (Index {start_idx:,}):")
+        print("-" * 50)
+        print(decoded_text)
+        print("-" * 50 + "\n")
+
+if __name__ == "__main__":
+    main()

val.bin

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+version https://git-lfs.github.com/spec/v1
+oid sha256:5c2a0206c7a25e384a365d21aee2391715ce4b45d4af9d65b2302fe344289e05
+size 8856490