aisingapore/llama-sea-lion-v3.5-8b-r-gguf overview

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    "library_name": "transformers",
    "pipeline_tag": "text-generation",
    "base_model": [
      "aisingapore/Llama-SEA-LION-v3-8B-IT"
    ],
    "language": [
      "en",
      "zh",
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    "license": "llama3.1",
    "frontmatter": {
      "library_name": "transformers",
      "pipeline_tag": "text-generation",
      "base_model": [
        "aisingapore/Llama-SEA-LION-v3-8B-IT"
      ],
      "language": [
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      "license": "llama3.1"
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    "hero_image_url": "llama_sea_lion_3.5_8b_r_banner.png",
    "summary": "SEA-LION is a collection of Large Language Models (LLMs) which have been pretrained and instruct-tuned for the Southeast Asia (SEA) region. SEA-LION stands for _Southeast Asian Languages In One Network_.",
    "quick_links": [],
    "benchmark_table_html": "",
    "readme_markdown": "---\nlibrary_name: transformers\npipeline_tag: text-generation\nbase_model:\n- aisingapore/Llama-SEA-LION-v3-8B-IT\nlanguage:\n- en\n- zh\n- vi\n- id\n- th\n- fil\n- ta\n- ms\n- km\n- lo\n- my\n- jv\n- su\nlicense: llama3.1\n---\n\n<div>\n  <img src=\"llama_sea_lion_3.5_8b_r_banner.png\"/>\n</div>\n\nCurrent Version: `14.04.2025`\n\n# Llama-SEA-LION-v3.5-8B-R\n\n[SEA-LION](https://arxiv.org/abs/2504.05747) is a collection of Large Language Models (LLMs) which have been pretrained and instruct-tuned for the Southeast Asia (SEA) region.\n\nSEA-LION stands for _Southeast Asian Languages In One Network_.\n\n- **Developed by:** Products Pillar, AI Singapore\n- **Funded by:** Singapore NRF\n- **Model type:** Decoder\n- **Languages supported:** Burmese, Chinese, English, Filipino, Indonesia, Javanese, Khmer, Lao, Malay, Sundanese, Tamil, Thai, Vietnamese\n- **License:** [Llama 3.1 Community License](https://huggingface.co/meta-llama/Llama-3.1-70B-Instruct/blob/main/LICENSE)\n\n## Description\n\nThis repo contains `GGUF` format model files for [aisingapore/Llama-SEA-LION-v3.5-8B-R](https://huggingface.co/aisingapore/Llama-SEA-LION-v3.5-8B-R).\n\n#### Model Weights Included in this repository:\n- [Llama-SEA-LION-v3.5-8B-R-F16](https://huggingface.co/aisingapore/Llama-SEA-LION-v3.5-8B-R-GGUF/blob/main/Llama-SEA-LION-v3.5-8B-R-F16.gguf)\n- [Llama-SEA-LION-v3.5-8B-R-Q2_K](https://huggingface.co/aisingapore/Llama-SEA-LION-v3.5-8B-R-GGUF/blob/main/Llama-SEA-LION-v3.5-8B-R-Q2_K.gguf)\n- [Llama-SEA-LION-v3.5-8B-R-Q3_K_M](https://huggingface.co/aisingapore/Llama-SEA-LION-v3.5-8B-R-GGUF/blob/main/Llama-SEA-LION-v3.5-8B-R-Q3_K_M.gguf)\n- [Llama-SEA-LION-v3.5-8B-R-Q4_0](https://huggingface.co/aisingapore/Llama-SEA-LION-v3.5-8B-R-GGUF/blob/main/Llama-SEA-LION-v3.5-8B-R-Q4_0.gguf)\n- [Llama-SEA-LION-v3.5-8B-R-Q4_K_M](https://huggingface.co/aisingapore/Llama-SEA-LION-v3.5-8B-R-GGUF/blob/main/Llama-SEA-LION-v3.5-8B-R-Q4_K_M.gguf)\n- [Llama-SEA-LION-v3.5-8B-R-Q5_0](https://huggingface.co/aisingapore/Llama-SEA-LION-v3.5-8B-R-GGUF/blob/main/Llama-SEA-LION-v3.5-8B-R-Q5_0.gguf)\n- [Llama-SEA-LION-v3.5-8B-R-Q5_K_M](https://huggingface.co/aisingapore/Llama-SEA-LION-v3.5-8B-R-GGUF/blob/main/Llama-SEA-LION-v3.5-8B-R-Q5_K_M.gguf)\n- [Llama-SEA-LION-v3.5-8B-R-Q6_K](https://huggingface.co/aisingapore/Llama-SEA-LION-v3.5-8B-R-GGUF/blob/main/Llama-SEA-LION-v3.5-8B-R-Q6_K.gguf)\n- [Llama-SEA-LION-v3.5-8B-R-Q8_0](https://huggingface.co/aisingapore/Llama-SEA-LION-v3.5-8B-R-GGUF/blob/main/Llama-SEA-LION-v3.5-8B-R-Q8_0.gguf)\n> [!NOTE]\n> Take note that some GGUFs are split into parts. Most tools such as [`llama.cpp`](https://github.com/ggerganov/llama.cpp) and those built on it do support split GGUFs, pointing the platform to the first split will be sufficient for it to function.\n> In the event where a merge is necessary, it can be done using `llama.cpp`'s `gguf-split`: `./gguf-split --merge ./path/to/first-split ./path/to/output-gguf`\n> More details: [gguf-split guide](https://github.com/ggerganov/llama.cpp/discussions/6404) & [README](https://github.com/ggerganov/llama.cpp/tree/master/examples/gguf-split)\n\n### Caveats\nIt is important for users to be aware that our model exhibits certain limitations that warrant consideration. Like many LLMs, the model can hallucinate and occasionally generates irrelevant content, introducing fictional elements that are not grounded in the provided context. Users should also exercise caution in interpreting and validating the model's responses due to the potential inconsistencies in its reasoning.\n\n## Limitations\n### Safety\nCurrent SEA-LION models, including this commercially permissive release, have not been aligned for safety. Developers and users should perform their own safety fine-tuning and related security measures. In no event shall the authors be held liable for any claim, damages, or other liability arising from the use of the released weights and codes.\n\n## Call for Contributions\nWe encourage researchers, developers, and language enthusiasts to actively contribute to the enhancement and expansion of SEA-LION. Contributions can involve identifying and reporting bugs, sharing pre-training, instruction, and preference data, improving documentation usability, proposing and implementing new model evaluation tasks and metrics, or training versions of the model in additional Southeast Asian languages. Join us in shaping the future of SEA-LION by sharing your expertise and insights to make these models more accessible, accurate, and versatile. Please check out our GitHub for further information on the call for contributions.\n\n## The Team\nAntonyrex Sajeban, Chan Adwin, Cheng Nicholas, Choa Esther, Huang Yuli, Hulagadri Adithya Venkatadri, Lau Wayne, Lee Chwan Ren, Leong Wai Yi, Leong Wei Qi, Liew Rachel, Limkonchotiwat Peerat, Liu Bing Jie Darius, Montalan Jann Railey, Ng Boon Cheong Raymond, Ngui Jian Gang, Nguyen Thanh Ngan, Ong Brandon, Ong Tat-Wee David, Ong Zhi Hao, Rengarajan Hamsawardhini, Siow Bryan, Susanto Yosephine, Tai Ngee Chia, Tan Choon Meng, Teng Walter, Teo Eng Sipp Leslie, Teo Wei Yi, Tjhi William, Yeo Yeow Tong, Yong Xianbin\n## Acknowledgements\n[AI Singapore](​​https://aisingapore.org/) is a national programme supported by the National Research Foundation, Singapore and hosted by the National University of Singapore. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not reflect the views of the National Research Foundation or the National University of Singapore. \n\n## Contact\nFor more info, please contact us using this [SEA-LION Inquiry Form](https://forms.gle/sLCUVb95wmGf43hi6)\n\n[Link to SEA-LION's GitHub repository](https://github.com/aisingapore/sealion)\n\n## Disclaimer\nThis is the repository for the commercial instruction-tuned model.\nThe model has _not_ been aligned for safety.\nDevelopers and users should perform their own safety fine-tuning and related security measures.\nIn no event shall the authors be held liable for any claims, damages, or other liabilities arising from the use of the released weights and codes. ",
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  "tags": [
    "transformers",
    "gguf",
    "text-generation",
    "en",
    "zh",
    "vi",
    "id",
    "th",
    "fil",
    "ta",
    "ms",
    "km",
    "lo",
    "my",
    "jv",
    "su",
    "arxiv:2504.05747",
    "base_model:aisingapore/Llama-SEA-LION-v3-8B-IT",
    "base_model:quantized:aisingapore/Llama-SEA-LION-v3-8B-IT",
    "license:llama3.1",
    "endpoints_compatible",
    "region:us",
    "conversational"
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  "last_modified": "2025-04-29T00:53:46.000Z",
  "created_at": "2025-04-28T04:50:06.000Z",
  "pipeline_tag": "text-generation",
  "library_name": "transformers"
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