crineforge 0.1.1

Forge intelligent models from raw data.

CrineForge

Forge intelligent text-trained models from raw documents.

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What is CrineForge?

CrineForge is a lightweight, offline-first LLM fine-tuning toolkit that automatically structures raw text data using a DeepSeek-based structurer and fine-tunes HuggingFace models using LoRA.

It is designed to be safe, modular, and GPU-aware.

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Who is it for?

• ML engineers
• AI developers
• Local model fine-tuning users
• Developers who want structured training without heavy setup

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Key Features

• DeepSeek-based structured data preparation
• LoRA fine-tuning support
• Automatic 4-bit fallback for low VRAM GPUs
• Gradient checkpointing
• VRAM usage logging
• CLI + Python API
• Offline-first design

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Quickstart

pip install crineforge

from crineforge import Trainer

trainer = Trainer()
trainer.connect_model("sshleifer/tiny-gpt2")
trainer.load_data("data.txt")
trainer.auto_config()
trainer.train()
trainer.save("output_model")

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Performance & Optimization

• Lazy-loaded structurer exclusively deployed at generation time.
• Structurer unloads natively before fine-tuning prevents VRAM spikes.
• Explicit gradient_checkpointing automatically supported.
• Automatic 4-bit quantization fallback detecting VRAM < 16GB.
• Comprehensive VRAM Logging tracking Allocated & Reserved metrics.
• Default max_seq_length = 512 enforcing scalable SFT executions.

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🔥 Important Disclaimer

Note:
CrineForge does not redistribute DeepSeek weights.
Models are downloaded from their official sources and are subject to their respective licenses.

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📄 License

Crineforge is licensed under the MIT License. Copyright (c) 2025 Abhishek.