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--- |
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license: other |
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license_name: tongyi-qianwen |
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license_link: >- |
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https://huggingface.co/Qwen/CodeQwen1.5-7B-Chat/blob/main/LICENSE |
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language: |
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- en |
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pipeline_tag: text-generation |
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tags: |
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- chat |
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--- |
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# Nxcode-CQ-7B-orpo |
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## Introduction |
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Nxcode-CQ-7B-orpo is an ORPO fine-tune of Qwen/CodeQwen1.5-7B-Chat on 100k samples ours datasets. |
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* Strong code generation capabilities and competitve performance across a series of benchmarks; |
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* Supporting 92 coding languages |
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* Excellent performance in text-to-SQL, bug fix, etc. |
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## Quickstart |
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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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"NTQAI/Nxcode-CQ-7B-orpo", |
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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("NTQAI/Nxcode-CQ-7B-orpo") |
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prompt = "Write a quicksort algorithm in python." |
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messages = [ |
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{"role": "system", "content": "You are a helpful assistant."}, |
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{"role": "user", "content": prompt} |
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] |
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text = tokenizer.apply_chat_template( |
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messages, |
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tokenize=False, |
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add_generation_prompt=True |
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) |
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model_inputs = tokenizer([text], return_tensors="pt").to(device) |
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generated_ids = model.generate( |
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model_inputs.input_ids, |
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max_new_tokens=512 |
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) |
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generated_ids = [ |
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output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids) |
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] |
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response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0] |
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``` |
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### Contact information |
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For personal communication related to this project, please contact Nha Nguyen Van (nha.nguyen@ntq-solution.com.vn). |
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