LydiaTM-SKL-32B

LydiaTM-SKL-32B is an advanced 32-billion parameter vision-language model developed by LydiaAI, specifically fine-tuned for SKL.

Model Description

This model represents a significant advancement in multimodal AI, combining state-of-the-art vision and language understanding capabilities. The model has been fine-tuned on a specialized SKL dataset to excel at complex reasoning tasks involving both visual and textual information.

Key Features:

  • 32B Parameters: Large-scale model for superior performance
  • FP8 Precision: Optimized quantization for efficient inference
  • Vision-Language Understanding: Advanced multimodal capabilities
  • Instruction Following: Sophisticated response to user instructions
  • Conversational AI: Natural dialogue capabilities
  • SKL Optimization: Specialized fine-tuning for knowledge-intensive tasks

Architecture:

  • Vision-Language Transformer architecture
  • Optimized attention mechanisms
  • Advanced tokenization for multimodal inputs
  • Efficient memory utilization with FP8 quantization

Usage

from transformers import AutoModel, AutoTokenizer, AutoProcessor
import torch

# Load model and processor
model = AutoModel.from_pretrained(
    "imhmdf/LydiaTM-SKL-32B",
    torch_dtype=torch.float16,
    device_map="auto",
    trust_remote_code=True
)

processor = AutoProcessor.from_pretrained(
    "imhmdf/LydiaTM-SKL-32B",
    trust_remote_code=True
)

tokenizer = AutoTokenizer.from_pretrained(
    "imhmdf/LydiaTM-SKL-32B",
    trust_remote_code=True
)

# Example usage for vision-language tasks
def process_image_text(image, text_prompt):
    inputs = processor(
        text=text_prompt,
        images=image,
        return_tensors="pt"
    )

    with torch.no_grad():
        outputs = model.generate(
            **inputs,
            max_length=512,
            do_sample=True,
            temperature=0.7
        )

    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
    return response

Training Details

Fine-tuning Process:

  • Specialized SKL dataset curation
  • Advanced fine-tuning techniques
  • Optimized hyperparameter tuning
  • Extensive validation and testing

Dataset:

  • High-quality multimodal training data
  • Diverse knowledge domains
  • Instruction-following examples
  • Conversational patterns

Performance

LydiaTM-SKL-32B demonstrates exceptional performance across various benchmarks:

  • Superior vision-language understanding
  • Advanced reasoning capabilities
  • Accurate instruction following
  • Natural conversational abilities

Intended Use

This model is designed for:

  • Research in multimodal AI
  • Educational applications
  • Knowledge-intensive tasks
  • Conversational AI systems
  • Vision-language applications

Limitations

  • Requires significant computational resources
  • May generate biased or incorrect information
  • Should be used responsibly with human oversight
  • Performance may vary across different domains

Ethics and Safety

LydiaAI is committed to responsible AI development. Users should:

  • Implement appropriate safety measures
  • Monitor outputs for potential biases
  • Use the model responsibly and ethically
  • Follow applicable AI ethics guidelines

License

This model is released under the Apache 2.0 license, allowing for both commercial and non-commercial use with appropriate attribution.

Citation

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

@model{LydiaTM-SKL-32B,
  title={LydiaTM-SKL-32B: Advanced Vision-Language Model for Specialized Knowledge Learning},
  author={LydiaAI Team},
  year={2026},
  url={https://huggingface.co/imhmdf/LydiaTM-SKL-32B}
}

Support

For technical support and questions, please visit our documentation or contact the LydiaAI team.


Developed by LydiaAI

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