Instructions to use mradermacher/Trinity-Large-Thinking-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mradermacher/Trinity-Large-Thinking-GGUF with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mradermacher/Trinity-Large-Thinking-GGUF", dtype="auto") - Notebooks
- Google Colab
- Kaggle
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| [PART 1](https://huggingface.co/mradermacher/Trinity-Large-Thinking-GGUF/resolve/main/Trinity-Large-Thinking.Q2_K.gguf.part1of3) [PART 2](https://huggingface.co/mradermacher/Trinity-Large-Thinking-GGUF/resolve/main/Trinity-Large-Thinking.Q2_K.gguf.part2of3) [PART 3](https://huggingface.co/mradermacher/Trinity-Large-Thinking-GGUF/resolve/main/Trinity-Large-Thinking.Q2_K.gguf.part3of3) | Q2_K | 144.9 | |
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| [P1](https://huggingface.co/mradermacher/Trinity-Large-Thinking-GGUF/resolve/main/Trinity-Large-Thinking.Q4_K_S.gguf.part1of5) [P2](https://huggingface.co/mradermacher/Trinity-Large-Thinking-GGUF/resolve/main/Trinity-Large-Thinking.Q4_K_S.gguf.part2of5) [P3](https://huggingface.co/mradermacher/Trinity-Large-Thinking-GGUF/resolve/main/Trinity-Large-Thinking.Q4_K_S.gguf.part3of5) [P4](https://huggingface.co/mradermacher/Trinity-Large-Thinking-GGUF/resolve/main/Trinity-Large-Thinking.Q4_K_S.gguf.part4of5) [P5](https://huggingface.co/mradermacher/Trinity-Large-Thinking-GGUF/resolve/main/Trinity-Large-Thinking.Q4_K_S.gguf.part5of5) | Q4_K_S | 225.0 | fast, recommended |
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| [P1](https://huggingface.co/mradermacher/Trinity-Large-Thinking-GGUF/resolve/main/Trinity-Large-Thinking.Q8_0.gguf.part1of9) [P2](https://huggingface.co/mradermacher/Trinity-Large-Thinking-GGUF/resolve/main/Trinity-Large-Thinking.Q8_0.gguf.part2of9) [P3](https://huggingface.co/mradermacher/Trinity-Large-Thinking-GGUF/resolve/main/Trinity-Large-Thinking.Q8_0.gguf.part3of9) [P4](https://huggingface.co/mradermacher/Trinity-Large-Thinking-GGUF/resolve/main/Trinity-Large-Thinking.Q8_0.gguf.part4of9) [P5](https://huggingface.co/mradermacher/Trinity-Large-Thinking-GGUF/resolve/main/Trinity-Large-Thinking.Q8_0.gguf.part5of9) [P6](https://huggingface.co/mradermacher/Trinity-Large-Thinking-GGUF/resolve/main/Trinity-Large-Thinking.Q8_0.gguf.part6of9) [P7](https://huggingface.co/mradermacher/Trinity-Large-Thinking-GGUF/resolve/main/Trinity-Large-Thinking.Q8_0.gguf.part7of9) [P8](https://huggingface.co/mradermacher/Trinity-Large-Thinking-GGUF/resolve/main/Trinity-Large-Thinking.Q8_0.gguf.part8of9) [P9](https://huggingface.co/mradermacher/Trinity-Large-Thinking-GGUF/resolve/main/Trinity-Large-Thinking.Q8_0.gguf.part9of9) | Q8_0 | 423.8 | fast, best quality |
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Here is a handy graph by ikawrakow comparing some lower-quality quant
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| [PART 1](https://huggingface.co/mradermacher/Trinity-Large-Thinking-GGUF/resolve/main/Trinity-Large-Thinking.Q2_K.gguf.part1of3) [PART 2](https://huggingface.co/mradermacher/Trinity-Large-Thinking-GGUF/resolve/main/Trinity-Large-Thinking.Q2_K.gguf.part2of3) [PART 3](https://huggingface.co/mradermacher/Trinity-Large-Thinking-GGUF/resolve/main/Trinity-Large-Thinking.Q2_K.gguf.part3of3) | Q2_K | 144.9 | |
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| [P1](https://huggingface.co/mradermacher/Trinity-Large-Thinking-GGUF/resolve/main/Trinity-Large-Thinking.Q4_K_S.gguf.part1of5) [P2](https://huggingface.co/mradermacher/Trinity-Large-Thinking-GGUF/resolve/main/Trinity-Large-Thinking.Q4_K_S.gguf.part2of5) [P3](https://huggingface.co/mradermacher/Trinity-Large-Thinking-GGUF/resolve/main/Trinity-Large-Thinking.Q4_K_S.gguf.part3of5) [P4](https://huggingface.co/mradermacher/Trinity-Large-Thinking-GGUF/resolve/main/Trinity-Large-Thinking.Q4_K_S.gguf.part4of5) [P5](https://huggingface.co/mradermacher/Trinity-Large-Thinking-GGUF/resolve/main/Trinity-Large-Thinking.Q4_K_S.gguf.part5of5) | Q4_K_S | 225.0 | fast, recommended |
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| [P1](https://huggingface.co/mradermacher/Trinity-Large-Thinking-GGUF/resolve/main/Trinity-Large-Thinking.Q6_K.gguf.part1of7) [P2](https://huggingface.co/mradermacher/Trinity-Large-Thinking-GGUF/resolve/main/Trinity-Large-Thinking.Q6_K.gguf.part2of7) [P3](https://huggingface.co/mradermacher/Trinity-Large-Thinking-GGUF/resolve/main/Trinity-Large-Thinking.Q6_K.gguf.part3of7) [P4](https://huggingface.co/mradermacher/Trinity-Large-Thinking-GGUF/resolve/main/Trinity-Large-Thinking.Q6_K.gguf.part4of7) [P5](https://huggingface.co/mradermacher/Trinity-Large-Thinking-GGUF/resolve/main/Trinity-Large-Thinking.Q6_K.gguf.part5of7) [P6](https://huggingface.co/mradermacher/Trinity-Large-Thinking-GGUF/resolve/main/Trinity-Large-Thinking.Q6_K.gguf.part6of7) [P7](https://huggingface.co/mradermacher/Trinity-Large-Thinking-GGUF/resolve/main/Trinity-Large-Thinking.Q6_K.gguf.part7of7) | Q6_K | 327.3 | very good quality |
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| [P1](https://huggingface.co/mradermacher/Trinity-Large-Thinking-GGUF/resolve/main/Trinity-Large-Thinking.Q8_0.gguf.part1of9) [P2](https://huggingface.co/mradermacher/Trinity-Large-Thinking-GGUF/resolve/main/Trinity-Large-Thinking.Q8_0.gguf.part2of9) [P3](https://huggingface.co/mradermacher/Trinity-Large-Thinking-GGUF/resolve/main/Trinity-Large-Thinking.Q8_0.gguf.part3of9) [P4](https://huggingface.co/mradermacher/Trinity-Large-Thinking-GGUF/resolve/main/Trinity-Large-Thinking.Q8_0.gguf.part4of9) [P5](https://huggingface.co/mradermacher/Trinity-Large-Thinking-GGUF/resolve/main/Trinity-Large-Thinking.Q8_0.gguf.part5of9) [P6](https://huggingface.co/mradermacher/Trinity-Large-Thinking-GGUF/resolve/main/Trinity-Large-Thinking.Q8_0.gguf.part6of9) [P7](https://huggingface.co/mradermacher/Trinity-Large-Thinking-GGUF/resolve/main/Trinity-Large-Thinking.Q8_0.gguf.part7of9) [P8](https://huggingface.co/mradermacher/Trinity-Large-Thinking-GGUF/resolve/main/Trinity-Large-Thinking.Q8_0.gguf.part8of9) [P9](https://huggingface.co/mradermacher/Trinity-Large-Thinking-GGUF/resolve/main/Trinity-Large-Thinking.Q8_0.gguf.part9of9) | Q8_0 | 423.8 | fast, best quality |
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Here is a handy graph by ikawrakow comparing some lower-quality quant
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