--- base_model: NCSOFT/Llama-VARCO-8B-Instruct library_name: transformers model_name: Llama-VARCO-8b-news2stock-analyser tags: - generated_from_trainer - trl - sft licence: license --- # Model Card for Llama-VARCO-8b-news2stock-analyser This model is a fine-tuned version of [NCSOFT/Llama-VARCO-8B-Instruct](https://huggingface.co/NCSOFT/Llama-VARCO-8B-Instruct). It has been trained using [TRL](https://github.com/huggingface/trl). ## Quick start ```python from transformers import pipeline question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?" generator = pipeline("text-generation", model="elsideks/Llama-VARCO-8b-news2stock-analyser", 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 SFT. ### Framework versions - TRL: 1.4.0 - Transformers: 5.9.0 - Pytorch: 2.8.0+cu128 - Datasets: 4.8.5 - Tokenizers: 0.22.2 ## 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} } ```
