Transformers
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sovereign-ai
ecological-intelligence
indian-llm
environmental-protection
Instructions to use iamkoder001/ARAVALLI-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use iamkoder001/ARAVALLI-1 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("iamkoder001/ARAVALLI-1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| import os | |
| import pymupdf4llm | |
| import pathlib | |
| import hashlib | |
| class SovereignCleaner: | |
| """ | |
| Cleans raw PDF ingestion and converts it to training-ready text. | |
| Ensures every document is hashed for the GOEC Audit Trail. | |
| """ | |
| def __init__(self, raw_dir="data/raw/", clean_dir="data/processed/texts/"): | |
| self.raw_dir = raw_dir | |
| self.clean_dir = clean_dir | |
| if not os.path.exists(self.clean_dir): | |
| os.makedirs(self.clean_dir) | |
| def _get_file_hash(self, filepath): | |
| """Generates SHA-256 hash to ensure the data is unfalsifiable.""" | |
| sha256_hash = hashlib.sha256() | |
| with open(filepath, "rb") as f: | |
| for byte_block in iter(lambda: f.read(4096), b""): | |
| sha256_hash.update(byte_block) | |
| return sha256_hash.hexdigest() | |
| def clean_all(self): | |
| """Iterates through raw PDFs and extracts structured text.""" | |
| files = [f for f in os.listdir(self.raw_dir) if f.endswith(".pdf")] | |
| print(f"Cleaning {len(files)} documents for ARAVALLI-1...") | |
| for file in files: | |
| raw_path = os.path.join(self.raw_dir, file) | |
| file_hash = self._get_file_hash(raw_path) | |
| # Use PyMuPDF4LLM for Markdown extraction (keeps tables/headings) | |
| try: | |
| md_text = pymupdf4llm.to_markdown(raw_path) | |
| # Metadata injection for the model's context | |
| header = f"--- SOURCE_HASH: {file_hash} ---\n" | |
| final_text = header + md_text | |
| clean_name = file.replace(".pdf", ".md") | |
| clean_path = os.path.join(self.clean_dir, clean_name) | |
| with open(clean_path, "w", encoding="utf-8") as f: | |
| f.write(final_text) | |
| print(f"Verified & Cleaned: {file}") | |
| except Exception as e: | |
| print(f"Failed to clean {file}: {e}") | |
| if __name__ == "__main__": | |
| cleaner = SovereignCleaner() | |
| cleaner.clean_all() | |