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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