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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
+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.
+
+