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Compute made for
chemists.

AI-DR is service-enhanced ImageDiffusion, Lyceum is the cloud-ready AI tool you've been waiting for.

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Built by scientists for scientists

🔥 NVIDIA B200s available now — contact us for pricing and availability.
Accelerate your AI research with the latest NVIDIA B200 GPUs. Perfect for large-scale diffusion models and image generation tasks.
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One-click GPU deployment.

Deploy your LoRA models and fine-tuned diffusers with zero infrastructure overhead. We handle the complex deployment so you can focus on your research.

Quick Setup
1 import torch
2 from diffusers import StableDiffusionPipeline
3 from peft import PeftModel
4 from henryr import InContextLoraClient
5
6 # Initialize client
7 client = InContextLoraClient(api_key="your_api_key")
8
9 # Load base model
10 base_model = StableDiffusionPipeline.from_pretrained(
11 "runwayml/stable-diffusion-v1-5",
12 torch_dtype=torch.float16
13 )
14
15 # Apply in-context LoRA
16 result = client.apply_lora(
17 base_model=base_model,
18 reference_image="your_logo.png",
19 target_image="target.jpg",
20 inpainting=True
21 )
22
23 # Save output
24 result.save("output.png")

Why switch and choose HenryR?

We've built the most efficient platform for AI-based image transformation, optimized for researchers and professional teams.

Other Clouds
⨯
Superfluous Pricing Models
⨯
Insufficient API Availability
⨯
Poor Developer Experience
⨯
Incomprehensible Billing
⨯
Dependency Lock-in
HenryR
✓
Transparent Usage-Based Pricing
✓
Robust API with Full Diffusers Support
✓
Simplified Development Workflow
✓
Predictable Cost Control
✓
Zero Vendor Lock-in Architecture

Our simple 3-step recipe for success.

Zero DevOps, zero infrastructure management, zero headaches. Just focus on building.

Smarter Scheduling

Advanced GPU allocation using Lyceum's proprietary scheduling algorithms, reducing wait times by up to 85% and increasing GPU utilization efficiency.

Effortless Usability

Build and deploy image transformation pipelines with our intuitive interface, designed for both beginners and experts. One-click deployments with zero infrastructure management.

Cost Control

Revolutionary cost optimization that automatically selects the most efficient hardware based on your workload. Our smart resource allocation saves up to 40% compared to standard cloud providers.

Frequently Asked Questions

How do I get started with Lyceum?
Getting started with HenryR's platform is simple. First, contact us using the form below to discuss your specific needs and receive API credentials. Once you have your API key, you can integrate our services using our Python client library. We offer comprehensive documentation and starter templates to help you implement In-Context LoRA, Image-to-Image, and Inpainting solutions quickly. Our team provides personalized onboarding to ensure you're up and running efficiently.
Will I incur ongoing hosting expenses?
No, one of the key advantages of our platform is that there are no ongoing hosting expenses for idle resources. Our pricing model is purely usage-based, meaning you only pay for the actual computation time your workloads consume. This eliminates the common cloud computing problem of paying for underutilized resources. We provide detailed usage analytics and cost estimation tools to help you predict and control your expenses.
How does In-Context LoRA differ from traditional approaches?
In-Context LoRA is our innovative approach that combines the adaptability of Low-Rank Adaptation (LoRA) with contextual understanding. Traditional fine-tuning requires extensive datasets and computational resources. In contrast, our In-Context LoRA can adapt models based on just a few reference images or even a single example. This approach dramatically reduces the time and resources needed for adaptation while maintaining high-quality results. It's particularly effective for tasks like logo application, style transfer, and domain-specific image generation where contextual understanding is crucial.
Do you support custom model deployment workflows?
Absolutely! We support fully customizable deployment workflows to match your specific research or production requirements. Our platform is designed to be flexible and can accommodate custom model architectures, novel diffusion techniques, and specialized inference pipelines. We support the full range of Hugging Face Diffusers models and allow for custom PyTorch implementations. Our team can work with you to optimize deployment for your specific use case, whether it's high-throughput batch processing or low-latency real-time applications.
What kind of hardware acceleration is available?
We offer a comprehensive range of hardware acceleration options to suit various workloads and budget requirements. Our platform includes access to the latest NVIDIA GPUs, including the new B200s for high-performance tasks. We also support multi-GPU configurations for distributed training and inference. Our intelligent scheduling system automatically selects the optimal hardware for your specific workload based on its characteristics, ensuring you get the best performance while optimizing costs. For specialized requirements, we can provision custom hardware configurations on request.

Ready to step into a
new era of compute?

If you want to take your image generation models to the next level, get in touch with us today.