--- base_model: - LiquidAI/LFM2.5-1.2B-Base tags: - text-generation-inference - transformers - unsloth - lfm2 license: apache-2.0 language: - en datasets: - unsloth/alpaca-cleaned - uniquealexx/Kimi-K2.6-Thinking-200x - nvidia/Nemotron-Cascade-2-SFT-Data - iamtarun/python_code_instructions_18k_alpaca - Entity-27th/ODIN-C1-SFT-Mix - Entity-27th/ODIN-C1-Realign ---  ODIN-C1(**O**n-**D**evice accelerated **I**ntelligent **N**etwork-**C**ode **1**) is a sLM engineered specifically for on-device programming. Based on LFM architecture, ODIN-C1 provides various advantages over other models such as hardware-agnostic inference affinity. ## Quick start ```python from transformers import pipeline question = "Can you write a simple Python script that shows the Fibonacci sequence?" generator = pipeline("text-generation", model="SKIS-AI-Research/ODIN-C1", device="cuda") output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0] print(output["generated_text"]) ``` ## Training procedure This model was trained with Supervised Fine-Tuning(SFT) on a single AMD Instinct MI300X accelerator and GeForce RTX 4070 Laptop GPU. ## Citations Cite TRL as: ```bibtex @software{vonwerra2020trl, title = {{TRL: Transformers Reinforcement Learning}}, author = {von Werra, Leandro and Belkada, Younes and Tunstall, Lewis and Beeching, Edward and Thrush, Tristan and Lambert, Nathan and Huang, Shengyi and Rasul, Kashif and Gallouédec, Quentin}, license = {Apache-2.0}, url = {https://github.com/huggingface/trl}, year = {2020} } `` This lfm2 model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library. [ ](https://github.com/unslothai/unsloth)
