Model: ubitech-edg/llava-7b-cpt-sft
Author: ubitech-edg
Pipeline: image-text-to-text
Library: transformers
Tags: transformers, safetensors, llava, image-to-text, multimodal, vision-language, supervised-fine-tuning, instruction-tuning, qa, lora, axolotl, deepspeed, eu-hpc, image-text-to-text, conversational, en, dataset:axolotl_deduplicated_synthetic_qa, dataset:mm_captions_chat, base_model:ubitech-edg/llava-7b-cpt, base_model:adapter:ubitech-edg/llava-7b-cpt, license:llama2, endpoints_compatible, region:us
Base models (adapter): id: ubitech-edg/llava-7b-cpt
Card metadata: language: en
license: llama2
tags: multimodal, vision-language, supervised-fine-tuning, instruction-tuning, qa, lora, axolotl, deepspeed, transformers, llava, eu-hpc
datasets: axolotl_deduplicated_synthetic_qa, mm_captions_chat
metrics: loss
library_name: transformers
framework: pytorch
base_model: ubitech-edg/llava-7b-cpt
model_name: llava-7b-cpt-sft
pipeline_tag: image-text-to-text
task_categories: image-text-to-text, visual-question-answering, text-generation
model_type: llava
inference: parameters: max_new_tokens: 512
temperature: 0.7
top_p: 0.9
trained_on: Leonardo EuroHPC
description: Final multimodal supervised fine-tuning (SFT) of LLaVA 7B, starting from the ubitech-edg/llava-7b-cpt model. The model refines both text and visual understanding on synthetic QA data using Axolotl and DeepSpeed ZeRO-1, producing a unified image–text reasoning assistant.
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Created: 2025-11-10 11:23:52