Hutton Tech Solutions Offers Long-Context Model Fine-Tuning

Hutton Tech Solutions provides a service for fine-tuning artificial intelligence models to handle long-context data. The company states that generic AI systems often forget information, whereas its service is designed to retain context by training models on a client's entire document library simultaneously. This approach allows the resulting AI to understand specific data and language nuances without losing context during operation. The training is conducted on local private infrastructure, ensuring that data does not leave the company's secure environment.

What the Service Includes

The company describes a complete deliverable package for its training projects. According to Hutton Tech Solutions, clients receive fine-tuned model weights in HuggingFace format, along with LoRA adapters if QLoRA training is utilized. The package also includes a tokenizer configuration optimized for the specific data, inference scripts in Python, API endpoints, and a Docker container to facilitate easy deployment.

Validation and documentation are part of the standard offering. The company says clients receive a training report featuring loss curves and metrics, as well as accuracy validation performed on a test set provided by the client. Sample outputs are included to demonstrate the learned behavior. Additionally, the package contains hyperparameter documentation, such as learning rate and batch size details, and an API integration guide for the client's application.

Pricing and Investment Tiers

Hutton Tech Solutions structures its services into three investment tiers, each with a one-time project fee that includes training, validation, and deployment support. The Starter tier is priced at $3,000. This option supports small-scale fine-tuning for models up to 13B parameters, such as Llama 3 8B or Mistral 7B. It allows for a 50k token context window during training and handles 10-20 documents in PDF, Word, or text formats. The company states this tier uses the QLoRA fine-tuning method and offers a 3-5 day turnaround.

The Professional tier is priced at $7,500 and is described as enterprise-grade training. This tier supports models up to 70B parameters, including Llama 3 70B or custom models, with a 100k+ token context window. It accommodates 50+ documents with unlimited pages and offers a choice between full fine-tuning or QLoRA. The company says this tier includes comprehensive accuracy testing using MMLU and custom evaluations, along with a 48-72 hour turnaround. It also provides two weeks of post-launch support for bug fixes and tuning.

The Enterprise tier has custom pricing and is designed for maximum capability. It supports 70B+ parameter models with unlimited context window capacity and unlimited documents, allowing for multi-domain training. The company states this tier includes priority processing with a 24-48 hour turnaround, custom evaluation frameworks, and production-grade API support with load balancing. It also features a 90-day optimization period, which includes retraining if needed, and a dedicated support channel via Slack or Discord.

Target Industries and Technical Approach

Hutton Tech Solutions identifies several sectors that may benefit from its long-context fine-tuning. The company lists legal firms, noting that the service can train on case law, contracts, and precedents to understand jurisdictional nuances. For medical research, the company says the service can ingest clinical trials, research papers, and patient data, with training that is HIPAA-compliant. The service is also marketed for enterprise knowledge, aiming to consolidate a company's documentation, policies, and institutional knowledge into a single AI system.

The company highlights its technical approach as a differentiator. It states that most providers cap context windows at 8k-32k tokens, which forces data chunking and loss of connections. In contrast, Hutton Tech Solutions trains with 100k+ tokens at once. The company also notes that it uses QLoRA on 70B models, allowing for the fine-tuning of massive models that typically require expensive cloud clusters, but at a fraction of the cost. The company emphasizes that its infrastructure completes training in 48-72 hours, contrasting this with the weeks often required by competitors.

To begin a project, the company requires documents such as PDFs, Word docs, or text files, which it handles during preprocessing. Clients must also define training objectives and select a base model, such as Llama 3, Mistral, or a custom model. Hutton Tech Solutions is a private company and is not listed on any stock exchange.

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Sources

• Hutton Tech Solutions: product page

Sponsored content from Hutton Tech Solutions. It was written with AI assistance from Hutton Tech Solutions' own materials and checked against them; claims are the company's. Cover image is AI-generated.