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README.md
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pinned: false
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---
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# The AI model built for deterministic developer tasks - Interfaze
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Interfaze is an AI model built on a new architecture that merges specialized DNN/CNN models with LLMs for developer tasks that require deterministic output and high consistency like OCR, scraping, classification, web search and more.
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```
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+===-----------------=++**++=---::::::::::::::::::::::::::::::--=+++++=-
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%##*=--------------:---==+***++=---::::::::::::::::::::::::::::::-=+****=:.:
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%%@%#===+++++++++++++++***#####*********++++++++++++++++++++++++++*######*=:::
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%@@@#+=+*#****##############################****************###%%%%%%%%@@#=::-
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%%@@#+-::=+******############%%%%%%%%%%%%%%######***********#%%%%%%%%%@@@%=::-
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%%@@*-:...-+#%%@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@%+--=
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%%@%+-....:%@@@@@@@@@@@@@%%%%%%%%#################******##%@@@@@@@@@@@@@@%**++
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%%@%+:....-%%%@@@@@@%%%%%%%%%%%################***********#%%@@@@@@@@@@@@@#*++
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%%@%+:....=%#%@@@@@@%%%%%%%%%################**************#%%@%@@@@@@@@@@#+==
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%%@%+:....+#%@@@@@@@%%%%%%%%%################****************#%%@@@@@@@%@@*+--
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%%%%=:...:%%@@@@@@@%%%%%%%%%%############%%%%%%%%%%%%##*+=-. .=#%@@@@@%@@#+==
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%%%%=:...-@%@@@@@@@@@@@@@%%%%%%%%##############################@@@@@@@%%%%#*==
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%%%%*+=--=%@%@@@@@@@@@%%%%%%%%%%%%%%%%#######################%@@@@@@@@%%%%#*==
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%%%%*+-:.:*%%%@@@@@@@@@%%%%%%%%%%%%%%%%%%###################%@@@@@@@@%%%%%#*+=
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##%#+-....+%%%@@@@@@@@@@%%%%%%%%%%%%%%%%%%%%%%%%%#########%%%@@@@@@@@%%%%%#*+=
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%#%#=:....-%%%@@@@@@@@@@@@@@@@%%%%%%%%%%%%%%%%%%%%%%%%%%%%%@@@@@@@@@@%%%%%#*+=
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%#%#=:.....-=+*#######%%%%%%@@@@@@@@@@@@@@@@@@@%%%%%%#####%%%%%%%@@@@@%%%%#*+=
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##%#=:.....:::--==++++===---::::::::::::::::::::::::::::::::-=++***##%@@@%#*+=
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####=:::-----------==+****++=-------------------:::::::::::::----=+**####%#*+=
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####=::::::::::::::--==+++=--::::::::::::::::::::::::...........::-+********+=
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####=::::::::::::::--=++++=--:::::::::::::::::::................::-+********++
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###*=::::::::::::::-==++++=--::::::::::::::::..:--:::------------=+*##*####*++
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##**=:::::::::::::--==++++=--::::::::::-*##*-::-==-:..:........:::-+***####*++
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#***+===============++++++==--------------:::::::::----------==+**##########
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#**************************++++++++++++++++++++++++++****##%%%%%%%%%%%%%
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###########################*******##########%%%%%%%%%%%%%%%###
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*+===+*#%%%%%####************+++++++++++++*##%%%%%%@@%######
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***#####%###*****++++++++++++++++++++++**#%%%%%%%%@@@@@@
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```
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* OCR, web scraping, web search, classification and more
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* OpenAI chat completion API compatible
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* High accuracy structured output consistency
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* Built-in code execution and sandboxing
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* Custom web engine for scraping and web research capabilities
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* Auto reasoning when needed
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* Controllable guardrails
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* Fully managed and scalable
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* Globally distributed fallback system with high uptime
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### Beta launch video
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[
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](https://x.com/yoeven/status/1975592154807624059)
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### Model Comparison
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* Benchmark: MMLU-Pro
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* interfaze-beta: 83.6
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* GPT-4.1: 80.6
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* Claude Sonnet 4: 83.7
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* Gemini 2.5 Flash: 80.9
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* Claude Sonnet 4 (Thinking): 83.7
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* Claude Opus 4 (Thinking): 86
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* GPT-5-Minimal: 80.6
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* Gemini-2.5-Pro: 86.2
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* Benchmark: MMLU
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* interfaze-beta: 91.38
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* GPT-4.1: 90.2
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* Claude Sonnet 4: -
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* Gemini 2.5 Flash: -
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* Claude Sonnet 4 (Thinking): 88.8
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* Claude Opus 4 (Thinking): 89
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* GPT-5-Minimal: -
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* Gemini-2.5-Pro: 89.2
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* Benchmark: MMMU
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* interfaze-beta: 77.33
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* GPT-4.1: 74.8
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* Claude Sonnet 4: -
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* Gemini 2.5 Flash: 79.7
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* Claude Sonnet 4 (Thinking): 74.4
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* Claude Opus 4 (Thinking): 76.5
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* GPT-5-Minimal: -
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* Gemini-2.5-Pro: 82
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* Benchmark: AIME-2025
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* interfaze-beta: 90
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* GPT-4.1: 34.7
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* Claude Sonnet 4: 38
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* Gemini 2.5 Flash: 60.3
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* Claude Sonnet 4 (Thinking): 74.3
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* Claude Opus 4 (Thinking): 73.3
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* GPT-5-Minimal: 31.7
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* Gemini-2.5-Pro: 87.7
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* Benchmark: GPQA-Diamond
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* interfaze-beta: 81.31
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* GPT-4.1: 66.3
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* Claude Sonnet 4: 68.3
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* Gemini 2.5 Flash: 68.3
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* Claude Sonnet 4 (Thinking): 77.7
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* Claude Opus 4 (Thinking): 79.6
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* GPT-5-Minimal: 67.3
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* Gemini-2.5-Pro: 84.4
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* Benchmark: LiveCodeBench
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* interfaze-beta: 57.77
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* GPT-4.1: 45.7
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* Claude Sonnet 4: 44.9
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* Gemini 2.5 Flash: 49.5
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* Claude Sonnet 4 (Thinking): 65.5
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* Claude Opus 4 (Thinking): 63.6
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* GPT-5-Minimal: 55.8
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* Gemini-2.5-Pro: 75.9
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* Benchmark: ChartQA
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* interfaze-beta: 90.88
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* GPT-4.1: -
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* Claude Sonnet 4: -
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* Gemini 2.5 Flash: -
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* Claude Sonnet 4 (Thinking): -
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* Claude Opus 4 (Thinking): -
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* GPT-5-Minimal: -
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* Gemini-2.5-Pro: -
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* Benchmark: AI2D
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* interfaze-beta: 91.51
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* GPT-4.1: 85.9
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* Claude Sonnet 4: -
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* Gemini 2.5 Flash: -
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* Claude Sonnet 4 (Thinking): -
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* Claude Opus 4 (Thinking): -
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* GPT-5-Minimal: -
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* Gemini-2.5-Pro: 89.5
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* Benchmark: Common-Voice-v16
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* interfaze-beta: 90.8
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* GPT-4.1: -
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* Claude Sonnet 4: -
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* Gemini 2.5 Flash: -
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* Claude Sonnet 4 (Thinking): -
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* Claude Opus 4 (Thinking): -
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* GPT-5-Minimal: -
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* Gemini-2.5-Pro: -
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\*Results for Non-Interfaze models are sourced from model providers, leaderboards, and evaluation providers such as Artificial Analysis.
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### Works like any other LLM
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OpenAI API compatible, works with every AI SDK out of the box
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OpenAI SDK
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Vercel AI SDK
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Langchain SDK
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Fully configurable guardrails for text and images
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This architecture combines a suite of small specialized models supported with custom tools and infrastructure while automatically routing to the best model for the task that prioritizes accuracy and speed.
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[
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](/examples/howitworks.png)
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### Specs
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Max output tokens
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32k tokens
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Input modalities
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Text, Images, Audio, File, Video
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Output tokens
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$3.50 / MTok
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Observability & Logging
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Coming soon
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### FAQ
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### Todo (Prioritized)
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* Reduce transactional token count
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* Pre-built prompts/schemas optimized for specific tasks
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* Embedding model
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* Built-in observability and logging on the dashboard
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* Complete metrics and analytics
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* v1.1 Interfaze
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* Reduce latency and improve throughput
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* Custom SDKs for interfaze with AI SDK, Langchain, etc.
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* Leaderboard for projects
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If you have feature requests or recommendations, please reach out!
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### Research references
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* [Interfaze: The Future of AI is built on Task-Specific Small Models](https://www.arxiv.org/abs/2602.04101)
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* [Agentic Context Engineering](https://www.arxiv.org/pdf/2510.04618)
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* [Small Language Models are the Future of Agentic AI](https://arxiv.org/pdf/2506.02153)
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* [The Sparsely-Gated Mixture-of-Experts Layer](https://arxiv.org/pdf/1701.06538)
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* [DeepSeekMoE](https://arxiv.org/pdf/2401.06066)
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* [Confronting LLMs with Traditional ML](https://arxiv.org/pdf/2310.14607)
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### Who are we?
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We are a small team of ML, Software and Infrastructure engineers engrossed in the fact that a small model can do a lot more when specialized. Allowing us to make AI available in every dev workflow.
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