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license: apache-2.0 |
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--- |
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## llama-2-7b-miniguanaco |
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This is my first model, with LLama-2-7b model finetuned with miniguanaco datasets. |
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This is a simple finetune based off a Google Colab notebook. Finetune instructions were from Labonne's first tutorial. |
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To run it: |
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import torch |
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from transformers import AutoTokenizer, AutoModelForCausalLM |
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import math |
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model_path = "decruz07/llama-2-7b-miniguanaco" |
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tokenizer = AutoTokenizer.from_pretrained(model_path, use_default_system_prompt=False) |
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model = AutoModelForCausalLM.from_pretrained( |
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model_path, torch_dtype=torch.float32, device_map='auto',local_files_only=False, load_in_4bit=True |
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) |
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print(model) |
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prompt = input("please input prompt:") |
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while len(prompt) > 0: |
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input_ids = tokenizer(prompt, return_tensors="pt").input_ids.to("cuda") |
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generation_output = model.generate( |
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input_ids=input_ids, max_new_tokens=500,repetition_penalty=1.2 |
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) |
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print(tokenizer.decode(generation_output[0])) |
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prompt = input("please input prompt:") |
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