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README.md

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+---
+license: mit
+task_categories:
+- text-generation
+language:
+- en
+tags:
+- brewing
+- non-alcoholic-beer
+- berkeley-yeast
+- nanochat
+size_categories:
+- 1K<n<10K
+---
+
+# Berkeley NA Brewing Corpus
+
+A text corpus about non-alcoholic beer brewing, created for training with [Karpathy's nanochat](https://github.com/karpathy/nanochat).
+
+## Dataset Description
+
+This dataset contains technical information about brewing non-alcoholic beer using Berkeley Yeast's maltose-negative yeast strains. The content covers:
+
+- Food safety best practices for NA beer production
+- Recipe development and mash procedures
+- Yeast selection and fermentation techniques
+- Pasteurization and packaging guidelines
+- Hop usage and flavor optimization
+
+## Sources
+
+The corpus is compiled from:
+- Berkeley Yeast technical documentation
+- Video transcripts from brewing tutorials
+- Webinar content on NA beer production
+
+## Usage
+
+### For nanochat pretraining
+
+```python
+# Load the raw text
+with open("train.txt", "r") as f:
+    corpus = f.read()
+```
+
+### With Hugging Face datasets
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("YOUR_USERNAME/berkeley-na-brewing-corpus")
+```
+
+## Format
+
+- `train.txt` - Combined plain text corpus
+- `train.jsonl` - JSON Lines format with "text" field
+- `train.parquet` - Parquet format (if available)
+
+## License
+
+MIT License