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View details ↗deepreinforce-ai_Ornith-1.0-35B-GGUF
bartowskiSome of these quants (Q3_K_XL, Q4_K_L etc) are the standard quantization method with the embeddings and output weights quantized to Q8_0 instead of what they would normally default to. If the model is bigger than 50GB, it will have been split into multiple files. In order to download them all to a local folder, run: You can either specify a new local-dir (deepreinforce-ai_Ornith-1.0-35B-Q8_0) or download them all in place (./)
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View details ↗deepreinforce-ai_Ornith-1.0-9B-GGUF
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View details ↗deepseek-ai_DeepSeek-R1-0528-GGUF
bartowskiHuge shoutout to Artus who helped with both conversion and imatrix calculation! All quants made using imatrix option with dataset from here Run them directly with llama.cpp, or any other llama.cpp based project
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View details ↗Some of these quants (Q3_K_XL, Q4_K_L etc) are the standard quantization method with the embeddings and output weights quantized to Q8_0 instead of what they would normally default to. If the model is bigger than 50GB, it will have been split into multiple files. In order to download them all to a local folder, run: You can either specify a new local-dir (deepseek-ai_DeepSeek-R1-0528-Qwen3-8B-Q8_0) or download them all in place (./)
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View details ↗deepseek-ai_DeepSeek-V3-0324-GGUF
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View details ↗deepseek-ai_DeepSeek-V3.1-Base-GGUF
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View details ↗deepseek-ai_DeepSeek-V3.1-GGUF
bartowskiAll quants made using imatrix option with dataset from here combined with a subset of combined_all_small.parquet from Ed Addario here Some of these quants (Q3_K_XL, Q4_K_L etc) are the standard quantization method with the embeddings and output weights quantized to Q8_0 instead of what they would normally default to. If the model is bigger than 50GB, it will have been split into multiple files. In order to download them all to a local folder, run:
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View details ↗deepseek-coder-1.3B-kexer-GGUF
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View details ↗deepseek-coder-6.7B-kexer-GGUF
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View details ↗DeepSeek-Coder-V2-Instruct-0724-GGUF
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View details ↗DeepSeek-Coder-V2-Instruct-GGUF
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View details ↗DeepSeek-Coder-V2-Lite-Base-GGUF
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View details ↗DeepSeek-Coder-V2-Lite-Instruct-GGUF
bartowskiOriginal model: https://huggingface.co/deepseek-ai/DeepSeek-Coder-V2-Lite-Instruct All quants made using imatrix option with dataset from here If the model is bigger than 50GB, it will have been split into multiple files. In order to download them all to a local folder, run:
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View details ↗DeepSeek-R1-Distill-Llama-70B-GGUF
bartowskiSome of these quants (Q3_K_XL, Q4_K_L etc) are the standard quantization method with the embeddings and output weights quantized to Q8_0 instead of what they would normally default to. If the model is bigger than 50GB, it will have been split into multiple files. In order to download them all to a local folder, run: You can either specify a new local-dir (DeepSeek-R1-Distill-Llama-70B-Q8_0) or download them all in place (./)
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View details ↗DeepSeek-R1-Distill-Llama-8B-GGUF
bartowskiSome of these quants (Q3_K_XL, Q4_K_L etc) are the standard quantization method with the embeddings and output weights quantized to Q8_0 instead of what they would normally default to. If the model is bigger than 50GB, it will have been split into multiple files. In order to download them all to a local folder, run: You can either specify a new local-dir (DeepSeek-R1-Distill-Llama-8B-Q8_0) or download them all in place (./)
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View details ↗DeepSeek-R1-Distill-Qwen-1.5B-GGUF
bartowskiAll quants made using imatrix option with dataset from here Some of these quants (Q3_K_XL, Q4_K_L etc) are the standard quantization method with the embeddings and output weights quantized to Q8_0 instead of what they would normally default to. If the model is bigger than 50GB, it will have been split into multiple files. In order to download them all to a local folder, run:
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View details ↗DeepSeek-R1-Distill-Qwen-14B-GGUF
bartowskiAll quants made using imatrix option with dataset from here Some of these quants (Q3_K_XL, Q4_K_L etc) are the standard quantization method with the embeddings and output weights quantized to Q8_0 instead of what they would normally default to. If the model is bigger than 50GB, it will have been split into multiple files. In order to download them all to a local folder, run:
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