Delete evaluate.py with huggingface_hub

evaluate.py

@@ -1,95 +0,0 @@
-# ==============================================================================
-# 🚀 ViuTranslate — Evaluation & Benchmark Suite
-# ==============================================================================
-
-import os
-import sys
-import json
-import time
-import torch
-from tokenizers import Tokenizer
-from huggingface_hub import hf_hub_download
-
-if hasattr(sys.stdout, "reconfigure"):
-    sys.stdout.reconfigure(encoding="utf-8", errors="replace")
-
-cur_dir = os.path.dirname(os.path.abspath(__file__)) if "__file__" in locals() else os.getcwd()
-if cur_dir not in sys.path:
-    sys.path.insert(0, cur_dir)
-
-from model import ViuAI
-from config import ViuAIConfig
-
-REPO_ID = "ViuAI/ViuTranslate"
-DATA_REPO_ID = "ViuAI/ViuTranslate-Data"
-EOT_ID = 64002
-
-def main():
-    print("=" * 80)
-    print("📊 ViuTranslate Benchmark Evaluation (Gold Human Test Set)")
-    print("=" * 80)
-    
-    device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
-    print(f"Device: {device.type.upper()}")
-    
-    # Load Model
-    ckpt_path = "viutranslate_final.pt"
-    if not os.path.exists(ckpt_path):
-        ckpt_path = hf_hub_download(repo_id=REPO_ID, filename="viutranslate_final.pt")
-        
-    tok_path = "tokenizer.json"
-    if not os.path.exists(tok_path):
-        tok_path = hf_hub_download(repo_id=REPO_ID, filename="tokenizer.json")
-        
-    tokenizer = Tokenizer.from_file(tok_path)
-    cfg = ViuAIConfig(vocab_size=64003, context_length=2048)
-    model = ViuAI(cfg).to(device)
-    
-    state = torch.load(ckpt_path, map_location=device, weights_only=False)
-    weights = state.get("model_state_dict", state)
-    model.load_state_dict(weights, strict=False)
-    model.eval()
-    print("✅ Model loaded.")
-    
-    # Download Validation Set
-    val_json_path = "raw/viu_translate_val.json"
-    if not os.path.exists(val_json_path):
-        try:
-            val_json_path = hf_hub_download(repo_id=DATA_REPO_ID, filename="raw/viu_translate_val.json", repo_type="dataset")
-        except Exception:
-            val_json_path = None
-            
-    if val_json_path and os.path.exists(val_json_path):
-        with open(val_json_path, 'r', encoding='utf-8') as f:
-            val_data = json.load(f)
-        print(f"Loaded {len(val_data):,} gold validation pairs.")
-    else:
-        print("Val JSON not found. Running curated benchmark cases.")
-        val_data = []
-
-    # Curated Benchmark Tests
-    benchmark_cases = [
-        ("The sun rises in the east and sets in the west.", "सूरज पूर्व में उगता है और पश्चिम में डूबता है।"),
-        ("Consistency and discipline are the keys to long term success.", "निरंतरता और अनुशासन दीर्घकालिक सफलता की कुंजी हैं।"),
-        ("Artificial intelligence is transforming industries across the globe.", "कृत्रिम बुद्धिमत्ता दुनिया भर के उद्योगों को बदल रही है।"),
-        ("Where is the nearest railway station?", "निकटतम रेलवे स्टेशन कहाँ है?"),
-        ("Regular exercise is essential for maintaining physical and mental health.", "शारीरिक और मानसिक स्वास्थ्य बनाए रखने के लिए नियमित व्यायाम आवश्यक है।")
-    ]
-    
-    print("\n🔍 Running Curated Test Cases:")
-    for en, hi_ref in benchmark_cases:
-        prompt = f"<|user|>\n{en}<|endofturn|>\n<|assistant|>\n"
-        inp = torch.tensor([tokenizer.encode(prompt).ids], device=device)
-        with torch.no_grad():
-            out = model.generate(inp, max_new_tokens=80, temperature=0.2, eos_token_id=EOT_ID)
-        gen = tokenizer.decode(out[0][inp.shape[1]:].tolist()).replace("<|endofturn|>", "").strip()
-        print(f"\n• EN:  {en}")
-        print(f"  REF: {hi_ref}")
-        print(f"  GEN: {gen}")
-
-    print("\n" + "=" * 80)
-    print("✅ Evaluation Completed!")
-    print("=" * 80)
-
-if __name__ == "__main__":
-    main()