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Deploying and Fine-Tuning an Uncensored DeepSeek R1 Distill Model on Google Cloud

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Aamazingandyyy
Last edited Jan 28, 2025
Created on Jan 29, 2025

This example demonstrates a complete workflow for deploying an uncensored DeepSeek R1 Distill model to Google Cloud Run with GPU support and fine-tuning it using a multi-stage pipeline. It includes a FastAPI inference server with `/v1/inference` and `/v1/finetune` endpoints, Docker configuration, and a fine-tuning process using Hugging Face Transformers and TRL that handles cold start data, reasoning reinforcement learning, and final tuning phases. The code shows concrete deployment commands using `gcloud run deploy` with `nvidia-l4` GPU specs, and processes JSONL training files for model customization.

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