--- library_name: transformers tags: - emotional-ai - ICONN - chatbot - base co2_eq_emissions: emissions: 0.34 source: CodeCarbon training_type: pretraining geographical_location: US-West hardware_used: 9 x B200 pipeline_tag: text-generation license: apache-2.0 ---

![ICONN AI Logo](https://i.postimg.cc/gJwHqh1D/svgviewer-png-output.png)

## ICONN 1 Introducing **ICONN 1 Mini Beta**, a cutting-edge open-source AI model with just **7 billion parameters** — designed for natural, human-like language understanding and generation. Despite its compact size, it delivers powerful performance through efficient architecture and careful tuning. ICONN 1 Mini Beta represents the next step in accessible, conversational AI. Developed entirely from scratch, ICONN-1-Mini-Beta is based on a new **ICONN** framework and comprises **7 billion parameters**. ICONN-1 is released in three distinct forms to serve different application needs: - **ICONN-1-Mini-Beta**(This model) is a small 7B model trained for a lightweight alternative to ICONN 1. - **ICONN-1** is optimized for natural, emotionally resonant, and conversational interactions. - **ICONN-e1** is a specialized variant of the model fine-tuned for advanced reasoning, critical analysis, and complex problem-solving. Together, these models represent a major leap forward in the evolution of AI systems—demonstrating not only deep reasoning but also a commitment to openness, accessibility, and human-aligned intelligence. ## Usage To run **ICONN 1 Mini Beta**, you need: - **Any hardware - CPU or GPU; Just make sure you have about 15GB storage space!** > Run the code below to run ICONN 1 Mini Beta: ```python import os import torch from transformers import AutoModelForCausalLM, AutoTokenizer, TextIteratorStreamer from threading import Thread model_id = "ICONNAI/ICONN-1-Mini-Beta" try: model = AutoModelForCausalLM.from_pretrained( model_id, torch_dtype=torch.float16, device_map="auto", trust_remote_code=True ) tokenizer = AutoTokenizer.from_pretrained(model_id) except Exception as e: exit(f"Exiting due to model loading error: {e}") def generate_response( message: str, max_new_tokens: int = 2048, temperature: float = 0.4, top_p: float = 0.9, top_k: int = 50, repetition_penalty: float = 1.2, ) -> str: conversation = [{"role": "user", "content": message}] try: input_ids = tokenizer.apply_chat_template( conversation, return_tensors="pt", enable_thinking=True ) except Exception as e: return f"Error applying chat template: {e}" input_ids = input_ids.to(model.device) streamer = TextIteratorStreamer(tokenizer, timeout=20.0, skip_prompt=True, skip_special_tokens=True) adjusted_top_k = int(max(1, top_k)) generate_kwargs = dict( {"input_ids": input_ids}, streamer=streamer, max_new_tokens=max_new_tokens, do_sample=True, top_p=top_p, top_k=adjusted_top_k, temperature=temperature, num_beams=1, repetition_penalty=repetition_penalty, ) try: t = Thread(target=model.generate, kwargs=generate_kwargs) t.start() except Exception as e: return f"Error starting generation thread: {e}" outputs = [] for text in streamer: outputs.append(text) return "".join(outputs) if __name__ == "__main__": question = "Can you explain briefly to me what is the Python programming language?" print(f"User Question: {question}") response = generate_response(question) print(f"Bot Response: {response}") ``` ## Cite Us **If you use ICONN 1, please cite us as follows:** ```DoI @misc{iconnai_2025, author = { ICONNAI }, title = { ICONN-1-Mini-Beta (Revision e29b435) }, year = 2025, url = { https://huggingface.co/ICONNAI/ICONN-1-Mini-Beta }, doi = { 10.57967/hf/5860 }, publisher = { Hugging Face } } ```