ZarfixAI/ZarfixAICerdas1.0

ZarfixAI Cerdas 1.0

Summary: ZarfixAI Cerdas 1.0 is a 4B parameter language model built for fast, efficient, and intelligent text generation. Optimized for practical applications where cost, speed, and accuracy matter.

Based on janhq/Jan-v1-4B. Original work is licensed under Apache-2.0 (see LICENSE in this repo).

🚀 Features

• —4B parameters for a balance between performance and efficiency
• —Supports instruction-following and general conversation
• —Runs on consumer GPUs or cloud T4 instances for low-cost deployment
• —Apache-2.0 license — flexible for commercial and personal projects

🛠️ Quickstart

from transformers import AutoTokenizer, AutoModelForCausalLM

model_id = "ZarfixAI/ZarfixAICerdas1.0"

tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id, device_map="auto")

prompt = "Explain the importance of renewable energy in simple terms."
inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
outputs = model.generate(**inputs, max_new_tokens=256)

print(tokenizer.decode(outputs[0], skip_special_tokens=True))

💡 Recommended Use Cases

• —Customer support bots
• —Knowledge assistants
• —Educational Q\&A
• —Creative writing prompts
• —Lightweight RAG (Retrieval-Augmented Generation) systems

⚠️ Limitations

• —The model may produce inaccurate or biased outputs — always verify important information.
• —Not fine-tuned for high-risk applications (medical, legal, financial advice).

📜 License

• —Original model: janhq/Jan-v1-4B under Apache-2.0 license.
• —ZarfixAI Cerdas 1.0: Derivative work under the same Apache-2.0 license.
• —You are free to use, modify, and deploy, but must keep attribution to the original authors.

🙏 Acknowledgements

Special thanks to the developers of janhq/Jan-v1-4B for providing a strong open-source foundation.