File size: 3,354 Bytes
1fa3c6c | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 | # Copyright 2020-2026 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from dataclasses import dataclass, field
from datasets import load_dataset
from huggingface_hub import ModelCard
from transformers import HfArgumentParser
@dataclass
class ScriptArguments:
r"""
Arguments for the script.
Args:
push_to_hub (`bool`, *optional*, defaults to `False`):
Whether to push the dataset to the Hugging Face Hub.
repo_id (`str`, *optional*, defaults to `"trl-lib/DeepMath-103K"`):
Hugging Face repository ID to push the dataset to.
dataset_num_proc (`int`, *optional*):
Number of workers to use for dataset processing.
"""
push_to_hub: bool = field(
default=False,
metadata={"help": "Whether to push the dataset to the Hugging Face Hub."},
)
repo_id: str = field(
default="trl-lib/DeepMath-103K",
metadata={"help": "Hugging Face repository ID to push the dataset to."},
)
dataset_num_proc: int | None = field(
default=None,
metadata={"help": "Number of workers to use for dataset processing."},
)
def process_example(example):
solution = example["final_answer"]
if solution not in ["True", "False", "Yes", "No"]:
solution = f"${solution}$"
prompt = [{"role": "user", "content": example["question"]}]
return {"prompt": prompt, "solution": solution}
model_card = ModelCard("""
---
tags: [trl]
---
# DeepMath-103K Dataset
## Summary
[DeepMath-103K](https://huggingface.co/datasets/zwhe99/DeepMath-103K) is meticulously curated to push the boundaries of mathematical reasoning in language models.
## Data Structure
- **Format**: [Conversational](https://huggingface.co/docs/trl/main/dataset_formats#conversational)
- **Type**: [Prompt-only](https://huggingface.co/docs/trl/main/dataset_formats#prompt-only)
Column:
- `"prompt"`: The input question.
- `"solution"`: The solution to the math problem.
## Generation script
The script used to generate this dataset can be found [here](https://github.com/huggingface/trl/blob/main/examples/datasets/deepmath_103k.py).
""")
if __name__ == "__main__":
parser = HfArgumentParser(ScriptArguments)
script_args = parser.parse_args_into_dataclasses()[0]
dataset = load_dataset("zwhe99/DeepMath-103K", split="train")
dataset = dataset.map(
process_example,
remove_columns=dataset.column_names,
num_proc=script_args.dataset_num_proc,
)
dataset = dataset.train_test_split(test_size=0.05, seed=42)
if script_args.push_to_hub:
dataset.push_to_hub(script_args.repo_id)
model_card.push_to_hub(script_args.repo_id, repo_type="dataset")
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