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README.md
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---
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license: apache-2.0
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---
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# P-Aligner
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## Quick Start
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```python
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import
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from transformers import AutoTokenizer
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raw_instruction = "What is the capital of France?"
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model_path = "
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tokenizer = AutoTokenizer.from_pretrained(model_path, trust_remote_code=True)
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model =
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model=model_path,
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gpu_memory_utilization=0.9,
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enable_prefix_caching=True,
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outputs = model.generate(
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[raw_instruction],
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)
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better_instruction = tokenizer.parse_output(
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outputs[0].outputs[0].text,
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---
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license: apache-2.0
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datasets:
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- songff/UltraPrompt
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language:
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- en
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base_model:
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- meta-llama/Llama-3.2-3B-Instruct
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library_name: transformers
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---
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# P-Aligner
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## Quick Start
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```python
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from vllm import LLM, SamplingParams
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from transformers import AutoTokenizer
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raw_instruction = "What is the capital of France?"
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model_path = "P-Aligner"
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tokenizer = AutoTokenizer.from_pretrained(model_path, trust_remote_code=True)
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model = LLM(
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model=model_path,
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gpu_memory_utilization=0.9,
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enable_prefix_caching=True,
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outputs = model.generate(
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[raw_instruction],
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sampling_params=SamplingParams(
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temperature=0.0,
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max_tokens=2048,
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),
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)
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better_instruction = tokenizer.parse_output(
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outputs[0].outputs[0].text,
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