Push Fine-Tuned Models to Hugging Face from Unsloth Studio

Melvin Vivas · X post · 2026-09-14 · Open on X

Topics: Fine-tuning & Model Customization, LLMOps, Deployment & Monitoring · Level: intermediate

Summary

After post-training, Unsloth Studio can upload your model to Hugging Face from its UI. You can also choose the quantizations.

Key points

• Unsloth Studio uploads post-trained models to the Hugging Face Hub from its UI.
• You can configure the quantizations (for example GGUF variants) before you upload.

Resources mentioned

• Unsloth · tool · unsloth.ai · free
  Open-source library for fast, memory-efficient fine-tuning of open LLMs (LoRA/QLoRA) on a single GPU or in Colab.
  Also in: Run Laya Decision models locally with Unsloth on 4GB RAM (Melvin Vivas on X · notes), Unsloth passes 500M model downloads on Hugging Face (Melvin Vivas on X · notes), Run Qwen-Image-2.1 locally on 12GB VRAM with Unsloth GGUFs (Melvin Vivas on X · notes), Base vs fine-tuned Gemma 4 E2B as a model router (Melvin Vivas on X · notes) and 29 more
• Hugging Face · website · x.com · free · recommended by both Bashiri Smith & Melvin Vivas
  Platform for hosting and finding ML models, datasets and papers. The quoted post says LocateAnything was trending there.
  Also in: Using an ML agent to train an open-source TTS model on your voice (Melvin Vivas on X · notes), Deploy Open-Source Models with Hugging Face Inference Endpoints (Melvin Vivas on X · notes), Deploying Qwen3.8 27B on Hugging Face Inference Endpoints (Melvin Vivas on X · notes), Using Hugging Face credits: Jobs, Inference Endpoints and Open Models (Melvin Vivas on X · notes) and 38 more

Try this

• After fine-tuning in Unsloth Studio, upload the model to Hugging Face from the UI with the quantizations you choose.