# Model Card for climategpt/climategpt-7b - This model is the 7B parameter variant of the ClimateGPT model release. ## Overview - **Developed by:** AppTek, Eqtylab, Erasmus AI - **Model type:** decoder-only Transformer - **Language(s) (NLP):** natively supported: English; supported via cascaded MT on web interface: Arabic, Bangla, Chinese (simplified), Dutch, Finnougoric, French, Germanic, Greek, Hebrew, Indonesian, Japenese, Korean, Lithuanian, Pashto, Persian, Portuguese, Russian, Spanish, Thai, Turkish, Vietnamese, - **License:** TO BE ADDED - **Finetuned from model:** Llama2 7B - **Repository:** https://huggingface.co/climategpt/climategpt-7b - **Paper:** TO BE ADDED - **Demo:** TO BE ADDED ## Uses - This model is intended to be directly used as a question answering model that is specialized in the climate domain. - The model is aimed at providing useful feedback for decision makers, scientists and jounalists involved in climate discussions. - The model can also be used as a starting point for interested developers for further finetuning. - The model is NOT intended to be a general-purpose chatbot (although it has chat capabilities). - For the full system including cascaded MT, RAG, etc., we recommend the user to go to our demo website: TO BE ADDED. - For hands-on finetuning deployment and inference, we recommend the user to directly use the Huggingface helpers. - For in-depth model conversion and finetuning, we recommend the user to use https://github.com/epfLLM/Megatron-LLM/. - **Despite the efforts from the development team to elimite them, as every other chat-capable LLMs, this model may generate biased, offensive, inaccurate responses.** ## How to Get Started with the Model After downloading the HF formatted model, the HF helpers should work out-of-the-box. It is also possible to evaluate the model with https://github.com/EleutherAI/lm-evaluation-harness by plugging in the model identifier ```--model_args pretrained=climategpt/climategpt-70b```. ## Training - For the Llama2 training data, we refer the user to https://huggingface.co/meta-llama/Llama-2-7b-hf. - For continued pretraining, 4.2B climate domain tokens (tokenized by the Llama tokenizer) are used. - For instruction finetuning, about 272K instruction-completion pairs (both in the climate domain but also general domain) are used. ## Environmental Impact - **Hardware Type:** H100 - **Hours used:** 230 hrs - **Cloud Provider:** TO BE ADDED - **Compute Region:** TO BE ADDED - **Carbon Emitted:** TO BE ADDED ## Citation **BibTeX:** TO BE ADDED