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--- |
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license: cc-by-sa-3.0 |
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task_categories: |
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- question-answering |
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- text-generation |
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language: |
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- en |
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size_categories: |
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- 10K<n<100K |
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--- |
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[databricks/databricks-dolly-15k](https://huggingface.co/datasets/databricks/databricks-dolly-15k) in ChatML format. |
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Python code used for conversion: |
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```python |
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from datasets import load_dataset |
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import pandas |
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from transformers import AutoTokenizer |
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tokenizer = AutoTokenizer.from_pretrained( |
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pretrained_model_name_or_path="Felladrin/Llama-160M-Chat-v1" |
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) |
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dataset = load_dataset("databricks/databricks-dolly-15k", split="train") |
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def format(columns): |
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instruction = columns["instruction"].strip() |
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context = columns["context"].strip() |
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response = columns["response"].strip() |
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if context: |
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user_message = f"{instruction}\n\nContext:\n{context}" |
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else: |
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user_message = instruction |
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messages = [ |
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{ |
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"role": "user", |
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"content": user_message, |
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}, |
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{ |
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"role": "assistant", |
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"content": response, |
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}, |
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] |
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return tokenizer.apply_chat_template(messages, tokenize=False) |
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pandas.DataFrame({"text": [format(columns) for columns in dataset]}).to_parquet("train.parquet", index=False) |
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``` |
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