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--- |
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license: apache-2.0 |
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--- |
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note : use original open llama tokenizer |
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#model_path = 'openlm-research/open_llama_3b' |
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model_path = 'ruwan/open-llama-sharded-1GB-7B-alpaca-vmware' |
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# model_path = 'openlm-research/open_llama_13b_600bt' |
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tokenizer = LlamaTokenizer.from_pretrained("openlm-research/open_llama_7b") |
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model = LlamaForCausalLM.from_pretrained( |
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model_path, torch_dtype=torch.float16, device_map='auto',load_in_8bit=True |
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) |
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prompt_template = "Below is an instruction that describes a task. Write a response that appropriately completes the request.\n\n### Instruction:\n{instruction}\n\n### Response:" |
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prompt= 'Explain in simple terms how the attention mechanism of a transformer model works' |
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inputt = prompt_template.format(instruction= prompt) |
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input_ids = tokenizer(inputt, return_tensors="pt").input_ids.to("cuda") |
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output1 = model.generate(input_ids, max_length=512) |
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input_length = input_ids.shape[1] |
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output1 = output1[:, input_length:] |
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output= tokenizer.decode(output1[0]) |
