Create README.md

README.md

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+---
+license: mit
+language:
+- zh
+tags:
+- creative-writing
+- novel
+task_categories:
+- text-generation
+pretty_name: Esjzone2024 8k
+---
+
+# Dataset Card for telecomadm1145/esjzone_2024
+
+## Dataset Details
+
+### Dataset Description
+
+Novels from Esjzone.
+
+Check [telecomadm1145/creative_writing](https://huggingface.co/datasets/telecomadm1145/creative_writing) for instruction finetuning and [telecomadm1145/esjzone_2024_chunked_8k](https://huggingface.co/datasets/telecomadm1145/esjzone_2024_chunked_8k) for continuation.
+
+- **Curated by:** telecomadm1145
+- **Language(s) (NLP):** Chinese
+- **License:** MIT
+
+### Dataset Sources
+
+- **Source Data:** Publicly available online novels (especially light novels).  
+
+---
+
+## Uses
+
+Better using DPP similar to below code:
+
+```py
+from datasets import load_dataset
+import random
+
+hf_dataset = load_dataset("telecomadm1145/esjzone_2024_chunked_8k", split="train")
+
+def make_prompt_response(example):
+    text = example["content"]
+
+    text = text[:3000] # TODO: Change if needed!
+
+    split_ratio = random.uniform(1/6, 1/2)
+    split_point = int(len(text) * split_ratio)
+    
+    context = text[:split_point]
+    continuation = text[split_point:]
+
+    user_message = f"""请按照这段文字的大致逻辑和剧情，以及人物发展，续写。直接输出后续的可能文段。
+```text
+{context}
+```"""
+    
+    prompt = f"<start_of_turn>user\n{user_message}<end_of_turn>\n<start_of_turn>model\n" # Chat template maybe different
+    
+    return {
+        "prompts": prompt,
+        "responses": continuation,
+    }
+
+hf_dataset = hf_dataset.map(make_prompt_response)
+```
+
+---
+
+## Dataset Structure
+
+- **Format:** JSON  
+- **Splits:**  
+  - `train`
+- **Fields:**  
+  - `book_title`: Title of the book.
+  - `chapter_title`: Title of the chapter.
+  - `content`: Content of the chapter.