Datasets:
Tasks:
Text Generation
Modalities:
Text
Sub-tasks:
language-modeling
Languages:
English
Size:
100K - 1M
License:
File size: 1,256 Bytes
72455b2 |
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from datasets import load_dataset
from itertools import islice
import sys
import time
from tqdm import tqdm
from transformers import AutoTokenizer
from itertools import islice
import json
NUM_PROC = 12
dataset = load_dataset("hoskinson-center/proof-pile")
tokenizer = AutoTokenizer.from_pretrained("EleutherAI/gpt-neox-20B")
def length(example):
return {"length": [len(x) for x in tokenizer(example["text"])["input_ids"]]}
dataset = dataset.map(length, batched=True, num_proc=NUM_PROC)
stats = dict()
for x in tqdm(dataset["train"]):
meta = json.loads(x["meta"])
if "config" in meta.keys():
config = meta["config"]
elif "set_name" in meta.keys():
config = meta["set_name"]
elif "subset_name" in meta.keys():
path = meta["file"]
config = path[:path.index("/")]
else:
print(x)
raise KeyError()
if config not in stats.keys():
stats[config] = dict()
stats[config]["bytes"] = 0
stats[config]["tokens"] = 0
stats[config]["bytes"] += len(x["text"].encode("utf-8"))
stats[config]["tokens"] += x["length"]
print(json.dumps(stats, indent=2))
print("saving stats...")
with open("stats.json", "w") as f:
f.write(json.dumps(stats, indent=2))
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