| from datasets import Dataset, load_dataset |
| from transformers import AutoTokenizer |
|
|
| tokenizer = AutoTokenizer.from_pretrained('models/RedPajama-INCITE-Instruct-7B') |
| max_seq = 2048 |
|
|
| def make_prompt(code): |
| 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' |
|
|
|
|
| def is_not_too_long(data): |
| encoded = tokenizer.encode(make_prompt(data['content'])) |
| return len(encoded) < max_seq |
|
|
| def deduplicate_dicts(dicts): |
| seen = {} |
| result = [] |
| for d in dicts: |
| content = d.get('content') |
| if content not in seen: |
| seen[content] = True |
| result.append(d) |
| return result |
|
|
| dataset = load_dataset('json', data_files='ts_parser/ts-chunks.jsonl') |
|
|
| data_short = dataset.filter(is_not_too_long) |
|
|
| dedup = deduplicate_dicts(data_short['train']) |
|
|
| data_short_dedup = Dataset.from_list(dedup) |
| print(data_short_dedup) |
|
|
| data_short_dedup.to_json('typescript-chunks.json') |
|
|
