Quantization made by Richard Erkhov. [Github](https://github.com/RichardErkhov) [Discord](https://discord.gg/pvy7H8DZMG) [Request more models](https://github.com/RichardErkhov/quant_request) Taiwan-LLM-7B-v2.0-base - GGUF - Model creator: https://huggingface.co/yentinglin/ - Original model: https://huggingface.co/yentinglin/Taiwan-LLM-7B-v2.0-base/ | Name | Quant method | Size | | ---- | ---- | ---- | | [Taiwan-LLM-7B-v2.0-base.Q2_K.gguf](https://huggingface.co/RichardErkhov/yentinglin_-_Taiwan-LLM-7B-v2.0-base-gguf/blob/main/Taiwan-LLM-7B-v2.0-base.Q2_K.gguf) | Q2_K | 2.36GB | | [Taiwan-LLM-7B-v2.0-base.IQ3_XS.gguf](https://huggingface.co/RichardErkhov/yentinglin_-_Taiwan-LLM-7B-v2.0-base-gguf/blob/main/Taiwan-LLM-7B-v2.0-base.IQ3_XS.gguf) | IQ3_XS | 2.6GB | | [Taiwan-LLM-7B-v2.0-base.IQ3_S.gguf](https://huggingface.co/RichardErkhov/yentinglin_-_Taiwan-LLM-7B-v2.0-base-gguf/blob/main/Taiwan-LLM-7B-v2.0-base.IQ3_S.gguf) | IQ3_S | 2.75GB | | [Taiwan-LLM-7B-v2.0-base.Q3_K_S.gguf](https://huggingface.co/RichardErkhov/yentinglin_-_Taiwan-LLM-7B-v2.0-base-gguf/blob/main/Taiwan-LLM-7B-v2.0-base.Q3_K_S.gguf) | Q3_K_S | 2.75GB | | [Taiwan-LLM-7B-v2.0-base.IQ3_M.gguf](https://huggingface.co/RichardErkhov/yentinglin_-_Taiwan-LLM-7B-v2.0-base-gguf/blob/main/Taiwan-LLM-7B-v2.0-base.IQ3_M.gguf) | IQ3_M | 2.9GB | | [Taiwan-LLM-7B-v2.0-base.Q3_K.gguf](https://huggingface.co/RichardErkhov/yentinglin_-_Taiwan-LLM-7B-v2.0-base-gguf/blob/main/Taiwan-LLM-7B-v2.0-base.Q3_K.gguf) | Q3_K | 3.07GB | | [Taiwan-LLM-7B-v2.0-base.Q3_K_M.gguf](https://huggingface.co/RichardErkhov/yentinglin_-_Taiwan-LLM-7B-v2.0-base-gguf/blob/main/Taiwan-LLM-7B-v2.0-base.Q3_K_M.gguf) | Q3_K_M | 3.07GB | | [Taiwan-LLM-7B-v2.0-base.Q3_K_L.gguf](https://huggingface.co/RichardErkhov/yentinglin_-_Taiwan-LLM-7B-v2.0-base-gguf/blob/main/Taiwan-LLM-7B-v2.0-base.Q3_K_L.gguf) | Q3_K_L | 3.35GB | | [Taiwan-LLM-7B-v2.0-base.IQ4_XS.gguf](https://huggingface.co/RichardErkhov/yentinglin_-_Taiwan-LLM-7B-v2.0-base-gguf/blob/main/Taiwan-LLM-7B-v2.0-base.IQ4_XS.gguf) | IQ4_XS | 3.4GB | | [Taiwan-LLM-7B-v2.0-base.Q4_0.gguf](https://huggingface.co/RichardErkhov/yentinglin_-_Taiwan-LLM-7B-v2.0-base-gguf/blob/main/Taiwan-LLM-7B-v2.0-base.Q4_0.gguf) | Q4_0 | 3.56GB | | [Taiwan-LLM-7B-v2.0-base.IQ4_NL.gguf](https://huggingface.co/RichardErkhov/yentinglin_-_Taiwan-LLM-7B-v2.0-base-gguf/blob/main/Taiwan-LLM-7B-v2.0-base.IQ4_NL.gguf) | IQ4_NL | 3.58GB | | [Taiwan-LLM-7B-v2.0-base.Q4_K_S.gguf](https://huggingface.co/RichardErkhov/yentinglin_-_Taiwan-LLM-7B-v2.0-base-gguf/blob/main/Taiwan-LLM-7B-v2.0-base.Q4_K_S.gguf) | Q4_K_S | 3.59GB | | [Taiwan-LLM-7B-v2.0-base.Q4_K.gguf](https://huggingface.co/RichardErkhov/yentinglin_-_Taiwan-LLM-7B-v2.0-base-gguf/blob/main/Taiwan-LLM-7B-v2.0-base.Q4_K.gguf) | Q4_K | 3.8GB | | [Taiwan-LLM-7B-v2.0-base.Q4_K_M.gguf](https://huggingface.co/RichardErkhov/yentinglin_-_Taiwan-LLM-7B-v2.0-base-gguf/blob/main/Taiwan-LLM-7B-v2.0-base.Q4_K_M.gguf) | Q4_K_M | 3.8GB | | [Taiwan-LLM-7B-v2.0-base.Q4_1.gguf](https://huggingface.co/RichardErkhov/yentinglin_-_Taiwan-LLM-7B-v2.0-base-gguf/blob/main/Taiwan-LLM-7B-v2.0-base.Q4_1.gguf) | Q4_1 | 3.95GB | | [Taiwan-LLM-7B-v2.0-base.Q5_0.gguf](https://huggingface.co/RichardErkhov/yentinglin_-_Taiwan-LLM-7B-v2.0-base-gguf/blob/main/Taiwan-LLM-7B-v2.0-base.Q5_0.gguf) | Q5_0 | 4.33GB | | [Taiwan-LLM-7B-v2.0-base.Q5_K_S.gguf](https://huggingface.co/RichardErkhov/yentinglin_-_Taiwan-LLM-7B-v2.0-base-gguf/blob/main/Taiwan-LLM-7B-v2.0-base.Q5_K_S.gguf) | Q5_K_S | 4.33GB | | [Taiwan-LLM-7B-v2.0-base.Q5_K.gguf](https://huggingface.co/RichardErkhov/yentinglin_-_Taiwan-LLM-7B-v2.0-base-gguf/blob/main/Taiwan-LLM-7B-v2.0-base.Q5_K.gguf) | Q5_K | 4.45GB | | [Taiwan-LLM-7B-v2.0-base.Q5_K_M.gguf](https://huggingface.co/RichardErkhov/yentinglin_-_Taiwan-LLM-7B-v2.0-base-gguf/blob/main/Taiwan-LLM-7B-v2.0-base.Q5_K_M.gguf) | Q5_K_M | 4.45GB | | [Taiwan-LLM-7B-v2.0-base.Q5_1.gguf](https://huggingface.co/RichardErkhov/yentinglin_-_Taiwan-LLM-7B-v2.0-base-gguf/blob/main/Taiwan-LLM-7B-v2.0-base.Q5_1.gguf) | Q5_1 | 4.72GB | | [Taiwan-LLM-7B-v2.0-base.Q6_K.gguf](https://huggingface.co/RichardErkhov/yentinglin_-_Taiwan-LLM-7B-v2.0-base-gguf/blob/main/Taiwan-LLM-7B-v2.0-base.Q6_K.gguf) | Q6_K | 5.15GB | | [Taiwan-LLM-7B-v2.0-base.Q8_0.gguf](https://huggingface.co/RichardErkhov/yentinglin_-_Taiwan-LLM-7B-v2.0-base-gguf/blob/main/Taiwan-LLM-7B-v2.0-base.Q8_0.gguf) | Q8_0 | 6.67GB | Original model description: --- license: apache-2.0 language: - zh widget: - text: "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: 你好，請問你可以幫我寫一封推薦信嗎？ ASSISTANT:" library_name: transformers pipeline_tag: text-generation extra_gated_heading: Acknowledge license to accept the repository. extra_gated_prompt: Please contact the author for access. extra_gated_button_content: Acknowledge license 同意以上內容 extra_gated_fields: Name: text Mail: text Organization: text Country: text Any utilization of the Taiwan LLM repository mandates the explicit acknowledgment and attribution to the original author: checkbox 使用Taiwan LLM必須明確地承認和歸功於優必達株式會社 Ubitus 以及原始作者: checkbox --- Taiwan LLM Logo # 🌟 Checkout [Taiwan-LLM Demo Chat-UI](http://www.twllm.com) 🌟 # Model Card for Taiwan LLM 7B v2.0 base Taiwan LLM is an advanced language model tailored for Traditional Chinese, focusing on the linguistic and cultural contexts of Taiwan. Developed from a large base model, it's enriched with diverse Taiwanese textual sources and refined through Supervised Fine-Tuning. This model excels in language understanding and generation, aligning closely with Taiwan's cultural nuances. It demonstrates improved performance on various benchmarks like TC-Eval, showcasing its contextual comprehension and cultural relevance. For detailed insights into Taiwan LLM's development and features, refer to our [technical report](https://github.com/MiuLab/Taiwan-LLaMa/blob/main/twllm_paper.pdf). ## Model description - **Model type:** A 7B parameter GPT-like model fine-tuned on a mix of publicly available, synthetic datasets. - **Language(s) (NLP):** Primarily Traditional Chinese (zh-tw) - **Finetuned from model:** [meta-llama/Llama-2-7b-hf](https://huggingface.co/yentinglin/meta-llama/Llama-2-7b-hf) ### Model Sources - **Repository:** https://github.com/MiuLab/Taiwan-LLaMa - **Demo:** https://twllm.com/ ## Performance ![image/png](https://cdn-uploads.huggingface.co/production/uploads/5df9c78eda6d0311fd3d541f/HTwIzw6RDha2-PhuWqSuI.png) ## Intended uses You should fine-tuned this model for instruction-following / chat application. ### Training hyperparameters ![image/png](https://cdn-uploads.huggingface.co/production/uploads/5df9c78eda6d0311fd3d541f/MdvHwdUvH-c926qyRAw7K.png) ![image/png](https://cdn-uploads.huggingface.co/production/uploads/5df9c78eda6d0311fd3d541f/kKpkvxDzOEyiAoTqmzRYO.png) ![image/png](https://cdn-uploads.huggingface.co/production/uploads/5df9c78eda6d0311fd3d541f/FsnlJ_fkRxf7fn5RKZnjE.png) The following hyperparameters were used during training: - learning_rate: 5e-05 - distributed_type: multi-GPU - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - lr_scheduler_warmup_ratio: 0.03 - num_epochs: 5.0 ## Citation If you find Taiwan LLM is useful in your work, please cite it with: ``` @misc{lin2023taiwan, title={Taiwan LLM: Bridging the Linguistic Divide with a Culturally Aligned Language Model}, author={Yen-Ting Lin and Yun-Nung Chen}, year={2023}, eprint={2311.17487}, archivePrefix={arXiv}, primaryClass={cs.CL} } ``` # Acknowledgement Taiwan LLM v2 is conducted in collaboration with [Ubitus K.K.](http://ubitus.net). Ubitus provides valuable compute resources for the project.