Upload latest Ray Peat embeddings (July 28, 2025 - 221826/221825 batch)

.gitattributes

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 # Video files - compressed
 *.mp4 filter=lfs diff=lfs merge=lfs -text
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+metadata_20250728_221826.json filter=lfs diff=lfs merge=lfs -text

README.md

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----
-license: mit
----
+# PeatLearn Embeddings Dataset
+
+This dataset contains pre-computed embeddings for the Ray Peat bioenergetic corpus used in the PeatLearn AI platform.
+
+## Files
+
+- `embeddings_20250728_221826.npy` - NumPy array of embeddings (310MB, latest complete run)
+- `metadata_20250728_221826.json` - Corresponding metadata and text chunks (21MB)
+- `ray_peat_embeddings_20250728_221825.pkl` - Pickled embeddings in alternative format (330MB)
+- `checkpoint.json` - Processing checkpoint information
+- `embedding_report.json` - Summary statistics and processing report
+
+## Usage
+
+```python
+# Download embeddings using the PeatLearn scripts
+python embedding/download_from_hf.py --repo abanwild/peatlearn-embeddings --dest embedding/vectors
+
+# Or using Hugging Face CLI
+hf download abanwild/peatlearn-embeddings --repo-type=dataset --local-dir embedding/vectors
+```
+
+## Model Information
+
+- **Embedding Model**: text-embedding-004 (Google)
+- **Dimensions**: 768
+- **Total Documents**: 552 Ray Peat documents
+- **Processing Date**: July 28, 2025
+
+## Repository
+
+Source code: https://github.com/thewildofficial/PeatLearn

embedding_report.json

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+{
+  "generation_completed": "2025-07-28T22:18:29.299477",
+  "total_pairs": 27664,
+  "successful_embeddings": 26431,
+  "failed_embeddings": 4,
+  "success_rate": 95.54294389820706,
+  "total_cost_usd": 0.7483,
+  "embedding_model": "gemini-embedding-001",
+  "embedding_dimensions": 768,
+  "processing_time_minutes": 13.79524495
+}

embeddings_20250728_221826.npy

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metadata_20250728_221826.json

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ray_peat_embeddings_20250728_221825.pkl

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