Top LLMs
- RP
- BF16
- rAIfle-SorcererLM-8x22b-bf16
- Context: 16K
- Recommended Settings: https://files.catbox.moe/9tj7m0.json
- RP, Storywriting. This model has spatial awareness, memory and detailed descriptions to keep the generation entertaining. Very good creativity and NSFW.
- FP8 Dynamic
- anthracite-org-magnum-v4-72b-FP8-Dynamic
- Context: 32k
- Preset: https://files.catbox.moe/rqei05.json
- RP Instruct: https://files.catbox.moe/btnhau.json
- RP Context: https://files.catbox.moe/7kct3f.json
Settings provided by: GERGE
- RP, Storywriting. Coherent, emotional and very creative.
- FP8 Dynamic
- L3.1-70B-Euryale-v2.2-FP8-Dynamic
- Context: 16K
- RP Instruct: https://files.catbox.moe/1c9sp0.json
- RP Context: https://files.catbox.moe/5wwpin.json
Settings provided by: ShotMisser64
Get immediate hands-on access to top LLMs using the familiar GPT interface you know.
Complete privacy and robust security, with no logging of prompts or model outputs. Use a single interface to explore multiple LLMs for your projects, research, or integrations.
How it Works
1. Discover
Get direct access to the best Large Language Models from Hugging Face’s LLM Leaderboard, all using the familiar user interface you know.
2. Choose your model
Test, tinker, and pinpoint the model that resonates with your content needs or business strategies.
3. Scale
As your needs evolve, Infermatic adapts. From niche projects to enterprise-level initiatives, the Infermatic platform scales with you. You’ll always have the right LLM tools at hand and at the scale you need.
Speed to market is critical, so don’t let setup slow you down.
We take the Ops out of MLOps.
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Infrastructure is off your critical path.
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Latency & cold starts
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Version control headaches
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Integration complexity
Effortlessly integrate ML models into your projects, regardless of differing tech stacks. Let seamless integration be your new normal.
Scalability concerns
Grow your projects without fear of scalability limitations. As your user numbers grow, our back end gracefully handles the surge.
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Why Infermatic?
Simple
Infermatic’s clean design is user-friendly and familiar, so you can focus on your work without the clutter of irrelevant features.
Privacy
Unlike some services, we don’t log your prompts or results. Your inputs remain yours, and not part of the LLM information base.
Unrestricted Results
Experiment without guardrails on a secure platform. Iterate your product to its full potential.
Scalable
Infermatic scales with your business so you have the necessary resources when you need them at each stage of your growth.
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We safeguard your data. Our systems are up to date and incorporate strong encryption end-to-end.
No Coding Necessary
Infermatic is intuitively designed for any user who can write a good prompt. Navigate with ease, focus on crafting your narratives or strategies, and let us manage the back end complexities.
LLMs Trained for Your Use Case
Engage with the same user interface you love from GPT, but without the limitation of only one LLM. Explore what’s possible, including LLMs trained specifically for your use case.
Automatic Model Versioning
Seamlessly manage and transition between model versions, ensuring that you always deploy the most updated and efficient version without the hassle of manual configuration and updating.
Real-Time Monitoring
Stay ahead with instant insights. Monitor model performance and health in real time, allowing for swift interventions and optimal operations.
Frequently Asked Questions from Geek to Geek
- What is prompt engineering, and why is it critical in working with LLMs?
- How can I design effective prompts for LLMs?
- What are some standard techniques used in prompt engineering?
- How does prompt length impact the output of an LLM?
- How do LLMs understand and generate human-like text?
- What is the difference between Llama, Mixtral, and Qwen?
- What are some examples of advanced use cases of prompt engineering with LLMs?
- How do I choose the best LLM model for my project?
- What are large language models, and how do they differ from traditional NLP models?
- Can LLMs write code well?