File size: 6,350 Bytes
1a0e08b 041e51f 1a0e08b c8b0318 1a0e08b 041e51f 1a0e08b 041e51f 1a0e08b 041e51f 1a0e08b 041e51f 1a0e08b 041e51f 1a0e08b 041e51f 1a0e08b 041e51f 1a0e08b 041e51f 1a0e08b 041e51f 1a0e08b 041e51f 1a0e08b 041e51f 1a0e08b 041e51f 1a0e08b 041e51f |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 |
---
library_name: transformers
pipeline_tag: text-generation
base_model:
- aisingapore/Llama-SEA-LION-v3-70B-IT
language:
- en
- zh
- vi
- id
- th
- fil
- ta
- ms
- km
- lo
- my
- jv
- su
license: llama3.1
---
<div>
<img src="llama_sea_lion_3.5_70b_r_banner.png"/>
</div>
Last updated: 2025-14-04
# Llama-SEA-LION-v3.5-70B-R-GGUF
[**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.
### Model Description
<!-- Provide a longer summary of what this model is. -->
SEA-LION stands for *Southeast Asian Languages In One Network*.
Quantization was performed on Llama-SEA-LION-v3.5-70B-R to produce optimized variants that reduce memory requirements
while maintaining model quality. These quantized models support inference on a range of consumer-grade GPUs
and are compatible with various inference engines.
For tokenization, the model employs the default tokenizer used in Llama 3.1-70B-Instruct.
- **Developed by:** Products Pillar, AI Singapore
- **Funded by:** Singapore NRF
- **Model type:** Decoder
- **Context length:** 128k tokens
- **Language(s):** Burmese, Chinese, English, Filipino, Indonesian, Javanese, Khmer, Lao, Malay, Sundanese, Tamil, Thai, Vietnamese
- **License:** [Llama 3.1 Community License](https://huggingface.co/meta-llama/Llama-3.1-70B-Instruct/blob/main/LICENSE)
- **Quantized from model:** Llama-SEA-LION-v3.5-70B-R
This repo contains `GGUF` format models files for [aisingapore/Llama-SEA-LION-v3.5-70B-R](https://huggingface.co/aisingapore/Llama-SEA-LION-v3.5-70B-R)
Model Weights included in this repository:
- [Llama-SEA-LION-v3.5-70B-R-F16](https://huggingface.co/aisingapore/Llama-SEA-LION-v3.5-70B-R-GGUF/blob/main/Llama-SEA-LION-v3.5-70B-R-F16-00001-of-00008.gguf)
- [Llama-SEA-LION-v3.5-70B-R-Q2_K](https://huggingface.co/aisingapore/Llama-SEA-LION-v3.5-70B-R-GGUF/blob/main/Llama-SEA-LION-v3.5-70B-R-Q2_K.gguf)
- [Llama-SEA-LION-v3.5-70B-R-Q3_K_M](https://huggingface.co/aisingapore/Llama-SEA-LION-v3.5-70B-R-GGUF/blob/main/Llama-SEA-LION-v3.5-70B-R-Q3_K_M.gguf)
- [Llama-SEA-LION-v3.5-70B-R-Q4_0](https://huggingface.co/aisingapore/Llama-SEA-LION-v3.5-70B-R-GGUF/blob/main/Llama-SEA-LION-v3.5-70B-R-Q4_0.gguf)
- [Llama-SEA-LION-v3.5-70B-R-Q4_K_M](https://huggingface.co/aisingapore/Llama-SEA-LION-v3.5-70B-R-GGUF/blob/main/Llama-SEA-LION-v3.5-70B-R-Q4_K_M.gguf)
- [Llama-SEA-LION-v3.5-70B-R-Q5_0](https://huggingface.co/aisingapore/Llama-SEA-LION-v3.5-70B-R-GGUF/blob/main/Llama-SEA-LION-v3.5-70B-R-Q5_0.gguf)
- [Llama-SEA-LION-v3.5-70B-R-Q5_K_M](https://huggingface.co/aisingapore/Llama-SEA-LION-v3.5-70B-R-GGUF/blob/main/Llama-SEA-LION-v3.5-70B-R-Q5_K_M.gguf)
- [Llama-SEA-LION-v3.5-70B-R-Q6_K](https://huggingface.co/aisingapore/Llama-SEA-LION-v3.5-70B-R-GGUF/blob/main/Llama-SEA-LION-v3.5-70B-R-Q6_K-00001-of-00003.gguf)
- [Llama-SEA-LION-v3.5-70B-R-Q8_0](https://huggingface.co/aisingapore/Llama-SEA-LION-v3.5-70B-R-GGUF/blob/main/Llama-SEA-LION-v3.5-70B-R-Q8_0-00001-of-00004.gguf)
> [!NOTE]
> Take note that some GGUFs are split into parts. Most tools such as 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. 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 More details:
> gguf-split guide & [README](https://github.com/ggerganov/llama.cpp/tree/master/examples/gguf-split)
## Evaluation
<!-- This section describes the evaluation protocols and provides the results. -->
### Test Results
For details on Llama-SEA-LION-v3.5-70B-R performance, please refer to the SEA-HELM leaderboard, [Leaderboard results on SEA-HELM](https://leaderboard.sea-lion.ai/).
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
The model has 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 claims, damages, or other liabilities arising from the use of the released weights and codes.
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
*The model was not tested for robustness against adversarial prompting.* It 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.
## More Information
This is the repository for the commercial instruction-tuned model.
The model has 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 claims, damages, or other liabilities arising from the use of the released weights and codes.
[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.
[Link to SEA-LION's GitHub repository](https://github.com/aisingapore/sealion)
For more info, please contact us at sealion@aisingapore.org
## Team
Antonyrex 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
## Contact
sealion@aisingapore.org |