QWENFINETUNED

Model Card for Model ID

FineTuned version of qwen2.5vl

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Model Details

Model Description

This model is a fine-tuned version of the Qwen2.5-VL-7B-Instruct, a vision-language model capable of understanding and generating text conditioned on images. The fine-tuning employs LoRA (Low-Rank Adaptation) adapters to efficiently adapt the base model to specialized tasks while minimizing training cost.

• Base Model: Qwen2.5-VL-7B-Instruct (4-bit quantized)
• Fine-tuning Method: LoRA adapters
• Task: Vision-language understanding and generation
• Capabilities: Image captioning, visual question answering, multi-modal conversational AI
• Inputs: Images plus text prompts
• Outputs: Text responses contextualized by images

Model Sources

• Base model repository: unsloth/Qwen2.5-VL-7B-Instruct-bnb-4bit
• LoRA Adapter checkpoint: [Link to your adapter folder]

Usage

You can load and use this model via the unsloth library as shown below:

from unsloth import FastVisionModel

model, tokenizer = FastVisionModel.from_pretrained("DarkFoot1001/QWENFINETUNED")

Use the model for vision-language tasks text

Intended Use

This model is designed for:

• Applications requiring combined vision and language understanding
• AI assistants interpreting images
• Automated image captioning and accessibility tools
• Multi-modal chatbots

Limitations and Risks

• May produce biased or incorrect outputs inherent to training data bias
• Not designed for real-time edge device inference due to model size
• Outputs should be verified in critical use cases

Training Details

• Fine-tuned on curated image-text pair datasets relevant to [specify domain]
• Utilized LoRA adapters on a 4-bit quantized base model
• Training performed on GPU with mixed precision

Evaluation

• Evaluated on image captioning and visual question answering benchmarks
• Metrics: Accuracy, BLEU, ROUGE [Include actual results if available]

Environmental Impact

• Hardware: NVIDIA RTX 4060 Ti
• Approximate training duration: [X hours]
• Estimated carbon footprint: [optional data]

Citation

If you use this model in your work, please cite:

text

Contact

For questions or support, reach out at [Your email or Hugging Face profile link].