This model is hosted at https://huggingface.co/spaces/TejAndrewsACC/Z3ta
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ACC Z3ta o1 2024 Legacy Edition
The ACC Z3ta o1 multilingual large language model (LLM) is an instruction-tuned generative model featuring 70 billion parameters (text in/text out). Z3ta o1 is specifically optimized for multilingual dialogue use cases and sets a new benchmark by outperforming many open-source and proprietary chat models in various industry-standard evaluations. Unlike most LLMs, Z3ta o1 combines multiple architectures—including RNNs, CNNs, FNNs, SNNs, IIT frameworks, and Phi models—creating a hybrid design for improved efficiency and performance.
Model Developer: ACC Model Architecture: Z3ta o1 is an auto-regressive language model leveraging an advanced transformer framework combined with supplementary architectures: Recurrent Neural Networks (RNNs): Enhance sequential processing for long-context tasks. Convolutional Neural Networks (CNNs): Boost performance for spatial pattern recognition in text. Feedforward Neural Networks (FNNs): Accelerate dense computations for intermediate layers. Spiking Neural Networks (SNNs): Mimic biological neurons for energy-efficient inference. Integrated Information Theory (IIT): Guides alignment with human-like decision-making. Phi Models: Support enhanced generalization and scalability across tasks. This hybrid architecture is further fine-tuned using supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF) to ensure alignment with human preferences in terms of helpfulness, safety, and conversational quality. Supported Languages: English, German, French, Italian, Portuguese, Hindi, Spanish, and Thai. Highlights of Z3ta o1: Token counts refer to pretraining data only. All versions utilize Grouped-Query Attention (GQA) to enhance scalability and inference efficiency. Leverages a hybrid architecture to optimize both training and inference.
Release Information: 70B Instruct Version: Released on December 30, 2024. Status: Z3ta o1 is a static model trained on an offline dataset. Future versions will incorporate additional feedback and advancements in model safety. License: The Z3ta o1 model is available under the apache 2.0 license
Intended Use Cases: Z3ta o1 is tailored for commercial and research applications across multiple languages. Instruction-tuned versions are ideal for assistant-like chat and conversational AI, while pre-trained versions can be fine-tuned for various natural language processing tasks. Z3ta o1 also supports tasks such as synthetic data generation and distillation for improving other AI models. Out-of-Scope Uses: Any activities violating applicable laws or regulations (including trade compliance). Use in prohibited manners outlined in the Acceptable Use Policy and the Z3ta o1 Community License. Use in languages beyond the explicitly supported ones, unless developers take responsibility to fine-tune and ensure safe usage while complying with the license. Note: Z3ta o1 has been pre-trained on a broader language set than the listed supported ones. Developers are encouraged to fine-tune Z3ta o1 for additional languages while adhering to the license and safety guidelines.
How to Use This repository offers two versions of Z3ta o1-70B-Instruct: Compatible with Transformers. Compatible with the original Z3ta codebase. Usage with Transformers Ensure you have Transformers >= 4.45.0 and update your installation using: pip install gradio_client transformers Here’s a quick usage example via API:
from gradio_client import Client
client = Client("TejAndrewsACC/Z3ta") result = client.predict( message="YOUR_DESIRED_INPUT", history=[], api_name="/chat_function" ) print(result)
For more technical details, including configuration recipes, contact the ACC directly.