Update README.md

README.md

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----
-license: mit
----
+---
+license: mit
+task_categories:
+- text-classification
+- question-answering
+- text-generation
+language:
+- en
+size_categories:
+- 10M<n<100M
+---
+
+# 📚 TinyWay-Gutenberg-Clean (Compressed Shards)
+
+A large-scale, high-quality English text dataset derived from Project Gutenberg.
+The corpus has been cleaned, normalized, deduplicated, segmented into fixed-length samples, and stored as compressed JSONL shards for efficient large-scale language model training.
+
+This dataset is intended for pretraining and experimentation with small and medium language models such as **TinyWay**, tokenizer training, and large-scale NLP research.
+
+---
+
+## 📦 Dataset Overview
+
+* **Name:** TinyWay-Gutenberg-Clean
+* **Current Release:** ~19 compressed shards (`.jsonl.gz`)
+* **Estimated Samples:** Tens of millions of text segments
+* **Language:** English
+* **Format:** Gzip-compressed JSON Lines (`.jsonl.gz`)
+* **Source:** Project Gutenberg (public domain books)
+* **License:** Public Domain
+* **Maintainer:** Shivam (NNEngine / ITM AIR Lab)
+
+Each record contains a clean text segment between **30 and 60 words**.
+
+Future releases will scale this dataset further (e.g., 100M+ samples).
+
+---
+
+## Data Format
+
+Each line is a JSON object:
+
+```json
+{
+  "id": "twg_000000012345",
+  "text": "Cleaned natural English text segment between thirty and sixty words.",
+  "word_count": 42,
+  "source": "gutenberg"
+}
+```
+
+### Fields
+
+| Field        | Description                    |
+| ------------ | ------------------------------ |
+| `id`         | Unique sample identifier       |
+| `text`       | Clean English text segment     |
+| `word_count` | Number of words in the segment |
+| `source`     | Data source identifier         |
+
+---
+
+##  Data Processing Pipeline
+
+The dataset was generated using a fully streaming pipeline to ensure scalability and low memory usage.
+
+### Processing Steps
+
+1. **Streaming Input**
+
+   * Text streamed from a Project Gutenberg mirror on Hugging Face.
+
+2. **Text Cleaning**
+
+   * Removed Gutenberg headers and footers.
+   * Removed chapter titles, page numbers, and boilerplate text.
+   * Normalized whitespace and line breaks.
+   * Removed non-ASCII and control characters.
+   * Filtered malformed or extremely short segments.
+
+3. **Segmentation**
+
+   * Text segmented into chunks of **30–60 words**.
+
+4. **Validation**
+
+   * Enforced word count limits.
+   * Filtered invalid or noisy segments.
+
+5. **Deduplication**
+
+   * Exact hash-based deduplication applied during generation.
+
+6. **Compression & Sharding**
+
+   * Data stored as `.jsonl.gz` shards for efficient disk usage and streaming.
+
+---
+
+##  How to Load the Dataset
+
+### Using Hugging Face Datasets (Streaming)
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset(
+    "NNEngine/TinyWay-Gutenberg-Clean",
+    split="train",
+    streaming=True
+)
+
+for i, sample in enumerate(dataset):
+    print(sample)
+    if i == 3:
+        break
+```
+
+---
+
+### Reading a Shard Manually
+
+```python
+import gzip
+import json
+
+with gzip.open("train-00000.jsonl.gz", "rt", encoding="utf-8") as f:
+    for _ in range(3):
+        print(json.loads(next(f)))
+```
+
+---
+
+##  Dataset Characteristics (Approximate)
+
+* **Average words per sample:** ~45
+* **Style:** Literary and narrative English
+* **Domain:** Fiction, non-fiction, historical texts
+* **Vocabulary:** Large natural English vocabulary
+* **Compression:** ~60–70% size reduction vs raw JSONL
+
+Exact statistics may vary per shard and will be expanded in future releases.
+
+---
+
+##  Limitations
+
+* Primarily literary and historical language.
+* No conversational chat data.
+* No code or structured technical documentation.
+* Some archaic vocabulary and sentence structures may appear.
+* Deduplication is hash-based (near-duplicates may remain).
+
+For conversational or web-style language modeling, this dataset should be mixed with complementary corpora.
+
+---
+
+## License
+
+All source texts originate from Project Gutenberg and are in the **public domain**.
+This processed dataset is released for unrestricted research and commercial use.
+
+---
+
+##  Versioning & Roadmap
+
+Planned future updates:
+
+- Larger releases (target: 100M+ samples)
+- Improved deduplication (near-duplicate filtering)
+- Dataset statistics and analytics
+- Additional language normalization
+
+Each major release will be versioned clearly.
+
+---
+
+## Citation
+
+If you use this dataset in research or publications, please cite:
+
+```
+TinyWay-Gutenberg-Clean
+Shivam (NNEngine), 2026
+```