| from transformers import BertModel, GPTNeoForCausalLM, AutoTokenizer | |
| def check_model(model_name, model_class, tokenizer_class): | |
| try: | |
| # Try loading the model | |
| model = model_class.from_pretrained(model_name) | |
| print(f"✅ {model_name} model loaded successfully.") | |
| except Exception as e: | |
| print(f"❌ Failed to load {model_name} model: {e}") | |
| try: | |
| # Try loading the tokenizer | |
| tokenizer = tokenizer_class.from_pretrained(model_name) | |
| print(f"✅ {model_name} tokenizer loaded successfully.") | |
| except Exception as e: | |
| print(f"❌ Failed to load {model_name} tokenizer: {e}") | |
| # Check BERT | |
| check_model("bert-base-uncased", BertModel, AutoTokenizer) | |
| # Check GPT-Neo | |
| check_model("EleutherAI/gpt-neo-125M", GPTNeoForCausalLM, AutoTokenizer) |