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