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AI 模型 84997
- NVIDIA-Nemotron-3.5-Lightning-30B-A3B-NVFP4-DFlash↗
NVIDIA
- tiny-random-ArceeForCausalLM↗
onnx-internal-testing
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).
- opus-mt-tc-big-en-pt-ct2-float16↗
ooeoeo
- Grug-67B-A2B-Datakit-SFT-262K-2026.09.21↗
open-athena
- InternVL3_5-241B-A28B-HF↗
OpenGVLab
- pvt_v2_b2_linear↗
OpenGVLab
- gpt-oss-20b-int4-ov↗
OpenVINO
- MediaPipe-Pose-Estimation↗
qualcomm
- Llama3.1-8B-Chinese-Chat-GGUF↗
QuantFactory
- N-ATLaS-GGUF↗
QuantFactory
N-ATLaS-LLM is a fine-tuned multilingual language model based on Llama-3 8B, specifically designed to support African languages, including Hausa, Igbo, and Yoruba alongside English. This model is powered by **Awarri Technologies** an initiative of the **Federal Ministry of Communications, Innovation and Digital Economy** as part of the Nigerian Languages AI Initiative to promote digital inclusion and preserve African linguistic heritage in the digital age. N-ATLaS-LLM is built on the Llama architecture and has been fine-tuned on over 400 million tokens of multilingual instruction data. The model demonstrates strong performance across multiple African languages while maintaining excellent English capabilities. N-ATLaS-LLM was trained on approximately **391,956,264 tokens** of quality multilingual instruction data.