| import torch | |
| from transformers import AutoModelForCausalLM, AutoTokenizer | |
| # Load the tokenizer and model from Hugging Face | |
| model_name = "impactframes/molmo-7B-D-bnb-4bit" | |
| tokenizer = AutoTokenizer.from_pretrained(model_name) | |
| model = AutoModelForCausalLM.from_pretrained(model_name) | |
| # Example input prompt | |
| prompt = "What is the meaning of life?" | |
| # Tokenize the input | |
| inputs = tokenizer(prompt, return_tensors="pt") | |
| # Generate output | |
| with torch.no_grad(): | |
| outputs = model.generate(inputs.input_ids, max_length=100) | |
| # Decode the output | |
| response = tokenizer.decode(outputs[0], skip_special_tokens=True) | |
| print(response) | |