Instructions to use DrGwin/Outputs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DrGwin/Outputs with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("DrGwin/Outputs", dtype="auto") - Notebooks
- Google Colab
- Kaggle
End of training
Browse files
README.md
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base_model: nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-BF16
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library_name: transformers
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model_name: Outputs
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tags:
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# Model Card for Outputs
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This model is a fine-tuned version of [nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-BF16](https://huggingface.co/nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-BF16).
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It has been trained using [TRL](https://github.com/huggingface/trl).
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## Quick start
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base_model: nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-BF16
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datasets: HuggingFaceH4/Multilingual-Thinking
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library_name: transformers
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model_name: Outputs
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tags:
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# Model Card for Outputs
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This model is a fine-tuned version of [nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-BF16](https://huggingface.co/nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-BF16) on the [HuggingFaceH4/Multilingual-Thinking](https://huggingface.co/datasets/HuggingFaceH4/Multilingual-Thinking) dataset.
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It has been trained using [TRL](https://github.com/huggingface/trl).
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## Quick start
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