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README.md
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library_name: transformers
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datasets:
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- PrimeIntellect/verifiable-coding-problems
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- likaixin/TACO-verified
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language:
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- en
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base_model:
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pipeline_tag: text-generation
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<div align="center">
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<span style="font-family: default; font-size: 1.5em;">DeepCoder-14B-Preview</span>
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<div>
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library_name: exllamav2
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datasets:
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- PrimeIntellect/verifiable-coding-problems
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- likaixin/TACO-verified
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language:
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- en
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base_model:
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- agentica-org/DeepCoder-14B-Preview
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pipeline_tag: text-generation
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# DeepCoder-14B-Preview-exl2
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Original model: [DeepCoder-14B-Preview](https://huggingface.co/agentica-org/DeepCoder-14B-Preview) by [Agentica](https://huggingface.co/agentica-org)
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Based on: [DeepSeek-R1-Distill-Qwen-14B](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-14B) by [DeepSeek](https://huggingface.co/deepseek-ai)
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Foundation model: [Qwen2.5-14B](https://huggingface.co/Qwen/Qwen2.5-14B) by [Qwen](https://huggingface.co/Qwen)
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## Quants
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[4bpw h6 (main)](https://huggingface.co/cgus/DeepCoder-14B-Preview-exl2/tree/main)
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[4.5bpw h6](https://huggingface.co/cgus/DeepCoder-14B-Preview-exl2/tree/4.5bpw-h6)
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[5bpw h6](https://huggingface.co/cgus/DeepCoder-14B-Preview-exl2/tree/5bpw-h6)
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[6bpw h6](https://huggingface.co/cgus/DeepCoder-14B-Preview-exl2/tree/6bpw-h6)
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[8bpw h8](https://huggingface.co/cgus/DeepCoder-14B-Preview-exl2/tree/8bpw-h8)
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## Quantization notes
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Made with Exllamav2 0.2.8 with default dataset.
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It can be used with TabbyAPI, Text-Generation-WebUI and requires RTX GPU on Windows or RTX/ROCm on Linux.
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RAM offloading isn't supported natively, so make sure it fits your GPU VRAM.
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I'd recommend at least a 12GB GPU for 4-5bpw quants.
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# Original model card
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<div align="center">
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<span style="font-family: default; font-size: 1.5em;">DeepCoder-14B-Preview</span>
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<div>
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