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from datasets import Dataset, load_dataset |
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from transformers import AutoTokenizer |
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tokenizer = AutoTokenizer.from_pretrained('models/RedPajama-INCITE-Instruct-7B') |
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max_seq = 2048 |
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def make_prompt(code): |
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return f'Below is an instruction that describes a task. Write a response that appropriately completes the request.\n\n### Instruction:\n{code}\n\n### Response:\n' |
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def is_not_too_long(data): |
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encoded = tokenizer.encode(make_prompt(data['content'])) |
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return len(encoded) < max_seq |
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def deduplicate_dicts(dicts): |
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seen = {} |
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result = [] |
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for d in dicts: |
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content = d.get('content') |
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if content not in seen: |
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seen[content] = True |
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result.append(d) |
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return result |
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dataset = load_dataset('json', data_files='ts_parser/ts-chunks.jsonl') |
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data_short = dataset.filter(is_not_too_long) |
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dedup = deduplicate_dicts(data_short['train']) |
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data_short_dedup = Dataset.from_list(dedup) |
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print(data_short_dedup) |
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data_short_dedup.to_json('typescript-chunks.json') |
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