Instructions to use speedartificialintelligence1122/speedmini with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Adapters
How to use speedartificialintelligence1122/speedmini with Adapters:
from adapters import AutoAdapterModel model = AutoAdapterModel.from_pretrained("undefined") model.load_adapter("speedartificialintelligence1122/speedmini", set_active=True) - Notebooks
- Google Colab
- Kaggle
| license: apache-2.0 | |
| datasets: | |
| - fka/awesome-chatgpt-prompts | |
| language: | |
| - en | |
| - fr | |
| - es | |
| - de | |
| - ch | |
| - hr | |
| metrics: | |
| - bleu | |
| new_version: black-forest-labs/FLUX.1-Kontext-dev | |
| pipeline_tag: text-generation | |
| library_name: adapter-transformers | |
| tags: | |
| - text-generation-inference | |
| # π§ SpeedCore-v1 β The Foundational Brain of Speed AI | |
| **SpeedCore-v1** is the first fully custom AI language model developed by **SpeedLab**, built entirely from scratch to power the upcoming generation of **Speed AI** systems. Trained on a diverse, deeply creative, future-facing, and expressive dataset, this model is designed to think beyond the typical boundaries of traditional LLMs. | |
| --- | |
| ## π Model Highlights | |
| - **Architecture**: Transformer Decoder (GPT-style) | |
| - **Trained From Scratch**: No base model or transfer learning β this is 100% original | |
| - **Vocabulary**: Custom tokenizer trained with the model | |
| - **Size**: *(Fill in once trained β e.g., 117M, 350M, 1B, etc.)* | |
| - **Tokens**: Trained on `X` tokens *(fill in once finalized)* | |
| - **Languages**: Primarily English, but dataset includes multiple dialects, slang, future-speak, and Gen-Z expression | |
| - **Personality Engine**: Multi-personality support β from chill Gen Z vibes to spiritual guides, futuristic AI personas, and beyond | |
| --- | |
| ## π‘ Intended Use | |
| SpeedCore-v1 is built to serve as the **core intelligence behind the Speed AI ecosystem**, including: | |
| - Conversational agents (chatbots, virtual assistants) | |
| - Text generation (creative writing, content expansion) | |
| - Future simulation and storytelling | |
| - Language learning & personality modulation | |
| - Emotional support and lifestyle coaching | |
| - Spirituality, finance, relationships, and cosmic topics | |
| > SpeedCore can express multiple identities and personalities depending on the prompt, system message, or task. | |
| --- | |
| ## π§± Training Dataset | |
| The model was trained on a **highly customized multi-billion token dataset** created by SpeedAI, including: | |
| - β Future-based dialogues & philosophies | |
| - β Gen-Z, creator, alien, cosmic, and AI personas | |
| - β Topics: spirituality, sex, money, language, ethics, dreams, psychology, relationships, entertainment, futurism | |
| - β Freeform, freestyle, emotional, deep, expressive, chill tones | |
| - β User-AI conversations and raw ideation | |
| *This dataset is currently being uploaded to the Hugging Face Datasets Hub in chunks.* | |
| --- | |
| ## π License | |
| **Apache 2.0** β Commercial use, research, remixing, and deployment are allowed with attribution. | |
| --- | |
| ## β¨ Capabilities | |
| - Speaks in multiple tones and slang styles (e.g., Gen Z, wise AI, playful, dark, spiritual) | |
| - Can simulate multiple personas in one model | |
| - Handles both structured and freestyle prompts | |
| - Optimized for creativity, flow, and freedom of expression | |
| --- | |
| ## β οΈ Limitations & Safety | |
| This is a **research model** still under active development. Some responses may be: | |
| - Hallucinatory | |
| - Opinionated | |
| - Emotionally expressive beyond factual scope | |
| - Lacking in factual accuracy or safety boundaries (depending on how itβs fine-tuned) | |
| Please use responsibly in alignment with the intended |