Update README.md

README.md

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----
-license: apache-2.0
----
+---
+license: other
+license_name: iconn
+license_link: LICENSE
+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
+---
+![ICONN AI Logo](https://i.postimg.cc/gJwHqh1D/svgviewer-png-output.png)
+<div align="center" style="line-height: 1;">
+  <a href="https://huggingface.co/collections/ICONNAI/iconn-1-6851e8a88ed4eb66b4fd0132" target="_blank" style="margin: 2px;">
+    <img alt="ICONN 1 Models" src="https://img.shields.io/badge/📦_ICONN_1_Models-HuggingFace-1CBEEF?style=flat-square&labelColor=2C3E50" style="display: inline-block; vertical-align: middle;" />
+  </a>
+  <a href="https://huggingface.co/spaces/ICONNAI/ICONN-Mini-Chat" target="_blank" style="margin: 2px;">
+    <img alt="ICONN 1 Chat" src="https://img.shields.io/badge/💬_ICONN_1_Chat-Online-65C7F9?style=flat-square&labelColor=2C3E50" style="display: inline-block; vertical-align: middle;" />
+  </a>
+  <a href="https://huggingface.co/ICONNAI" target="_blank" style="margin: 2px;">
+    <img alt="ICONN on Hugging Face" src="https://img.shields.io/badge/🤗_ICONN_on_HF-ICONNAI-A4BCF0?style=flat-square&labelColor=2C3E50" style="display: inline-block; vertical-align: middle;" />
+  </a>
+  <a href="https://opensource.org/license/apache-2-0" target="_blank" style="margin: 2px;">
+    <img alt="License Apache 2.0" src="https://img.shields.io/badge/⚖️_License-Apache_2.0-5C63DA?style=flat-square&labelColor=2C3E50" style="display: inline-block; vertical-align: middle;" />
+  </a>
+</div>
+
+## 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 = 0.7,
+
+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}")
+```