Q.Can I create my own retrieval model with Exthalpy?
A.Yes, you can build agents as well as models using Exthalpy for free.
H
HyperLLM - Hybrid Retrieval Transformers
★3.2
💬71
💲Paid
HyperLLM provides small language models with hybrid retrieval transformers for instant fine-tuning and training at 85% less cost. It uses serverless embedding and real-time retrieval to offer decentralized, zero-latency model training and deployment.
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Platform
web
Chatbot EnhancementContent RecommendationDecentralized AIHybrid Retrieval TransformersInstant Fine-tuningKnowledge ManagementMarket Intelligence
What is HyperLLM - Hybrid Retrieval Transformers?
HyperLLM is a new generation of Small Language Models called 'Hybrid Retrieval Transformers' that works with hyper-retrieval and world-class serverless embedding to power instant fine-tuning and training, at 85% less cost. It offers real-time retrieval for instant model fine-tuning, making AI model tuning and training accessible to everyone with no additional costs or training time. Exthalpy is the variable for hyperparameter control over HRTs.
Core Technologies
- Hybrid Retrieval Transformers
- Serverless Embedding
- Real-time Retrieval
- Hyperparameter Control
- Decentralized AI
Key Capabilities
- Instant fine-tuning and training
- Real-time retrieval argumentation
- Zero-latency retrieval architecture
- Training-independent models
- Semantic search capabilities
Use Cases
- Enhance chatbot systems with real-time information retrieval
- Build niche market intelligence models with semantic search
- Implement real-time enterprise knowledge management
- Gather real-time market research data for product management
- Create AI models for CRM systems with real-time customer insights
Core Benefits
- Cost-effective model training
- No recurring storage charges
- Zero tuning and training time
- Truly serverless and decentralized
- Always real-time and updated embeddings
Key Features
- Hybrid Retrieval Transformers (HRT) model architecture
- Real-time retrieval argumentation
- Serverless vector database for complete decentralization
- Zero-latency retrieval architecture (HyperRetrieval)
- Hyperparameter control with the Exthalpy variable
- Instant model fine-tuning and training
How to Use
- 1Get started with free access and explore use cases
- 2Integrate Exthalpy into your stacks with documentation and API references
- 3Build models using multiple source URLs to create embeddings and answer queries
Frequently Asked Questions
Q.Can I use my model with API?
A.All Hybrid Retrieval Models come with their own individual API set, model ID & API key. You can use it or share access with other users.
Q.Can I custom label my API URL?
A.White-labelling Exthalpy API URLs is currently an invite-only option too. But you can contact our team to get priority access of this feature.
Q.Can I use more than 1 source URL as data source?
A.Yes, models that you build with Exthalpy can use multiple source URLs to create embeddings and answer to queries.
Pros & Cons (Reserved)
✓ Pros
- 85% less cost than top LLMs
- Zero recurring storage charges
- Zero tuning & training time
- Truly server-less and decentralized
- Always real-time and updated embeds
- Training-independent models
✗ Cons
- Potential limitations for achieving singularity (unspecified)
- White-labelling API URLs is currently an invite-only option
Alternatives
No alternatives found.