Fine-tuning for Qwen 2.5 VL vision-language models, with up to 64K context

You can now fine-tune Vision-Language Models (VLMs) on Fireworks AI using the Qwen 2.5 VL model family. This extends our Supervised Fine-tuning V2 platform to support multimodal training with both images and text data.

Supported models:

• Qwen 2.5 VL 3B Instruct
• Qwen 2.5 VL 7B Instruct
• Qwen 2.5 VL 32B Instruct
• Qwen 2.5 VL 72B Instruct

Features:

• Fine-tune on datasets containing both images and text in JSONL format with base64-encoded images
• Support for up to 64K context length during training
• Built on the same Supervised Fine-tuning V2 infrastructure as text models

See the VLM fine-tuning documentation for setup instructions and dataset formatting requirements.