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README.md
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Here provides a code snippet with `apply_chat_template` to show you how to load the tokenizer and model and how to generate contents.
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```python
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from
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device = "cuda" # the device to load the model onto
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model = AutoModelForCausalLM.from_pretrained(
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"
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torch_dtype="auto",
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device_map="auto"
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)
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tokenizer = AutoTokenizer.from_pretrained("
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prompt = "Write a quicksort algorithm in python."
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messages = [
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Here provides a code snippet with `apply_chat_template` to show you how to load the tokenizer and model and how to generate contents.
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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device = "cuda" # the device to load the model onto
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model = AutoModelForCausalLM.from_pretrained(
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"study-hjt/CodeQwen1.5-7B-Chat-GPTQ-Int4",
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torch_dtype="auto",
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device_map="auto"
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)
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tokenizer = AutoTokenizer.from_pretrained("study-hjt/CodeQwen1.5-7B-Chat-GPTQ-Int4")
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prompt = "Write a quicksort algorithm in python."
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messages = [
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