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README.md
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</div>
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# Gemma Coder
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**Gemma 2B** fine-tuned on the **CodeAlpaca 20k instructions dataset** by using the method **QLoRA** with [PEFT](https://github.com/huggingface/peft) library.
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## Model description 🧠
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def generate(
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instruction,
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max_new_tokens=
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temperature=0.1,
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top_p=0.75,
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top_k=40,
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num_beams=
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**kwargs,
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):
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inputs = tokenizer(prompt, return_tensors="pt")
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input_ids = inputs["input_ids"].to("cuda")
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attention_mask = inputs["attention_mask"].to("cuda")
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attention_mask=attention_mask,
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generation_config=generation_config,
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return_dict_in_generate=True,
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output_scores=True,
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max_new_tokens=max_new_tokens,
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early_stopping=True
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)
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s = generation_output.sequences[0]
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output = tokenizer.decode(s)
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return output.split("
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instruction = """
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Edit the following XML code to add a navigation bar to the top of a web page
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</div>
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# Gemma Coder 👩💻
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**Gemma 2B** fine-tuned on the **CodeAlpaca 20k instructions dataset** by using the method **QLoRA** with [PEFT](https://github.com/huggingface/peft) library.
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## Model description 🧠
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def generate(
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instruction,
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max_new_tokens=256,
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temperature=0.1,
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top_p=0.75,
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top_k=40,
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num_beams=2,
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**kwargs,
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):
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system = f"<bos><|system|>\nYou are a helpful coding assistant.<eos>\n"
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prompt = f"{system}<|user|>\n{instruction}<eos>\n<|assistant|>\n"
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inputs = tokenizer(prompt, return_tensors="pt")
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input_ids = inputs["input_ids"].to("cuda")
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attention_mask = inputs["attention_mask"].to("cuda")
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attention_mask=attention_mask,
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generation_config=generation_config,
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return_dict_in_generate=True,
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#output_scores=True,
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max_new_tokens=max_new_tokens,
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early_stopping=True
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)
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s = generation_output.sequences[0]
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output = tokenizer.decode(s, skip_special_tokens=True)
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return output.split("<|assistant|>")[1]
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instruction = """
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Edit the following XML code to add a navigation bar to the top of a web page
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