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README.md

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----
-license: apache-2.0
----
+# JSON Mermaid Dataset
+
+This dataset contains conversations in ShareGPT format, designed for fine-tuning language models.
+
+## Dataset Structure
+
+The dataset follows the ShareGPT format, with each example containing a "conversations" field with an array of messages. Each message has:
+- "from": Indicates who sent the message (typically "human" or "gpt")
+- "value": The content of the message
+
+Example:
+```json
+{
+  "conversations": [
+    {"from": "human", "value": "Hello, how are you?"},
+    {"from": "gpt", "value": "I'm doing well, thank you for asking! How can I help you today?"}
+  ]
+}
+```
+
+## Usage
+
+You can load this dataset using the Hugging Face datasets library:
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("mugivara1/json-mermaid", split="train")
+```
+
+## Citation
+
+If you use this dataset in your research, please cite:
+
+```
+@misc{json-mermaid,
+  author = {mugivara1},
+  title = {JSON Mermaid Dataset},
+  year = {2025},
+  publisher = {GitHub},
+  url = {https://huggingface.co/datasets/mugivara1/json-mermaid}
+}
+```

data/combined_dataset.jsonl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:47b715d52cc55009e9a1c463c6b4724c3360f5c70d4bf57a260a399f259ec002
+size 106820118

json_mermaid.py

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+# coding=utf-8
+# Copyright 2023 The HuggingFace Datasets Authors.
+#
+# 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.
+
+import json
+import os
+
+import datasets
+
+_DESCRIPTION = """
+ShareGPT format conversations dataset for fine-tuning language models.
+"""
+
+_CITATION = """\
+@misc{json-mermaid,
+  author = {mugivara1},
+  title = {JSON Mermaid Dataset},
+  year = {2025},
+  publisher = {GitHub},
+  url = {https://huggingface.co/datasets/mugivara1/json-mermaid}
+}
+"""
+
+_HOMEPAGE = "https://huggingface.co/datasets/mugivara1/json-mermaid"
+
+# No URL since we are uploading files directly
+_URLs = {}
+
+
+class JsonMermaidConfig(datasets.BuilderConfig):
+    """BuilderConfig for JsonMermaid."""
+
+    def __init__(self, **kwargs):
+        """BuilderConfig for JsonMermaid.
+        Args:
+          **kwargs: keyword arguments forwarded to super.
+        """
+        super(JsonMermaidConfig, self).__init__(**kwargs)
+
+
+class JsonMermaid(datasets.GeneratorBasedBuilder):
+    """ShareGPT format conversations for LLM fine-tuning."""
+
+    VERSION = datasets.Version("1.0.0")
+    BUILDER_CONFIGS = [
+        JsonMermaidConfig(
+            name="default",
+            version=VERSION,
+            description="ShareGPT format conversations",
+        ),
+    ]
+    DEFAULT_CONFIG_NAME = "default"
+
+    def _info(self):
+        features = datasets.Features({
+            "conversations": datasets.Sequence(
+                {
+                    "from": datasets.Value("string"),
+                    "value": datasets.Value("string"),
+                }
+            ),
+        })
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            homepage=_HOMEPAGE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        data_dir = "data"
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "filepath": os.path.join(data_dir, "combined_dataset.jsonl"),
+                    "split": "train",
+                },
+            ),
+        ]
+
+    def _generate_examples(self, filepath, split):
+        """Yields examples."""
+        with open(filepath, encoding="utf-8") as f:
+            for idx, line in enumerate(f):
+                data = json.loads(line)
+                # Handle the ShareGPT format - either directly use the conversations array
+                # or create one from the specified format in your data
+                if "conversations" in data:
+                    conversations = data["conversations"]
+                else:
+                    # If your data has a different structure, adapt this part
+                    # This assumes each line is a list of messages in the format [{"from": "...", "value": "..."}]
+                    conversations = data
+
+                yield idx, {
+                    "conversations": conversations,
+                }