| |
| """ |
| Script to pre-download T5 models with extended timeout settings |
| """ |
|
|
| import os |
| import time |
| from transformers import AutoTokenizer, AutoModelForSeq2SeqLM |
|
|
| def download_t5_model(): |
| """Download T5-base model and tokenizer with extended timeout""" |
| |
| |
| os.environ['HF_HUB_TIMEOUT'] = '300' |
| os.environ['REQUESTS_TIMEOUT'] = '300' |
| |
| print("Downloading T5-base model and tokenizer...") |
| print("This may take several minutes depending on your connection...") |
| |
| try: |
| print("Step 1/2: Downloading tokenizer...") |
| tokenizer = AutoTokenizer.from_pretrained('t5-base') |
| print("✅ Tokenizer downloaded successfully") |
| |
| print("Step 2/2: Downloading model...") |
| model = AutoModelForSeq2SeqLM.from_pretrained('t5-base') |
| print("✅ Model downloaded successfully") |
| |
| print("🎉 All models downloaded and cached!") |
| print("You can now run the training scripts offline.") |
| |
| return True |
| |
| except Exception as e: |
| print(f"❌ Download failed: {e}") |
| print("\n💡 Alternative solutions:") |
| print("1. Try again with better internet connection") |
| print("2. Use a VPN if there are regional restrictions") |
| print("3. Download manually from: https://huggingface.co/t5-base") |
| return False |
|
|
| if __name__ == "__main__": |
| success = download_t5_model() |
| if success: |
| print("\n✅ Ready for training! You can now run:") |
| print(" powershell -ExecutionPolicy Bypass -File scripts/test_small_training.ps1") |
| else: |
| print("\n⚠️ Please fix connectivity and try again") |
