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Model: mradermacher/Qwen2.5-7B-Instruct-1M-Thinking-Claude-Gemini-GPT5.2-DISTILL-GGUF Source: Original Platform
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README.md
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---
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base_model: DavidAU/Qwen2.5-7B-Instruct-1M-Thinking-Claude-Gemini-GPT5.2-DISTILL
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datasets:
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- TeichAI/claude-4.5-opus-high-reasoning-250x
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- TeichAI/gemini-3-pro-preview-high-reasoning-250x
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- TeichAI/gpt-5.2-high-reasoning-250x
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language:
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- en
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- fr
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- de
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- es
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- it
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- pt
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- ru
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- zh
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- ja
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library_name: transformers
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mradermacher:
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readme_rev: 1
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quantized_by: mradermacher
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tags:
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- thinking
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- reasoning
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- Gemini
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- Claude Opus
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- Gpt5.2
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- Distill
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- finetune
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- creative
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- creative writing
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- fiction writing
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- plot generation
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- sub-plot generation
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- fiction writing
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- story generation
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- scene continue
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- storytelling
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- fiction story
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- science fiction
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- romance
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- all genres
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- story
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- writing
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- vivid prose
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- vivid writing
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- fiction
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- roleplaying
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- bfloat16
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- swearing
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- rp
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- horror
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- unsloth
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- context 1 million
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---
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## About
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<!-- ### quantize_version: 2 -->
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<!-- ### output_tensor_quantised: 1 -->
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<!-- ### convert_type: hf -->
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<!-- ### vocab_type: -->
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<!-- ### tags: -->
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<!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->
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<!-- ### quants_skip: -->
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<!-- ### skip_mmproj: -->
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static quants of https://huggingface.co/DavidAU/Qwen2.5-7B-Instruct-1M-Thinking-Claude-Gemini-GPT5.2-DISTILL
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<!-- provided-files -->
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***For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#Qwen2.5-7B-Instruct-1M-Thinking-Claude-Gemini-GPT5.2-DISTILL-GGUF).***
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weighted/imatrix quants are available at https://huggingface.co/mradermacher/Qwen2.5-7B-Instruct-1M-Thinking-Claude-Gemini-GPT5.2-DISTILL-i1-GGUF
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## Usage
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If you are unsure how to use GGUF files, refer to one of [TheBloke's
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READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for
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more details, including on how to concatenate multi-part files.
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## Provided Quants
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(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)
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| Link | Type | Size/GB | Notes |
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|:-----|:-----|--------:|:------|
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| [GGUF](https://huggingface.co/mradermacher/Qwen2.5-7B-Instruct-1M-Thinking-Claude-Gemini-GPT5.2-DISTILL-GGUF/resolve/main/Qwen2.5-7B-Instruct-1M-Thinking-Claude-Gemini-GPT5.2-DISTILL.Q2_K.gguf) | Q2_K | 3.1 | |
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| [GGUF](https://huggingface.co/mradermacher/Qwen2.5-7B-Instruct-1M-Thinking-Claude-Gemini-GPT5.2-DISTILL-GGUF/resolve/main/Qwen2.5-7B-Instruct-1M-Thinking-Claude-Gemini-GPT5.2-DISTILL.Q3_K_S.gguf) | Q3_K_S | 3.6 | |
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| [GGUF](https://huggingface.co/mradermacher/Qwen2.5-7B-Instruct-1M-Thinking-Claude-Gemini-GPT5.2-DISTILL-GGUF/resolve/main/Qwen2.5-7B-Instruct-1M-Thinking-Claude-Gemini-GPT5.2-DISTILL.Q3_K_M.gguf) | Q3_K_M | 3.9 | lower quality |
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| [GGUF](https://huggingface.co/mradermacher/Qwen2.5-7B-Instruct-1M-Thinking-Claude-Gemini-GPT5.2-DISTILL-GGUF/resolve/main/Qwen2.5-7B-Instruct-1M-Thinking-Claude-Gemini-GPT5.2-DISTILL.Q3_K_L.gguf) | Q3_K_L | 4.2 | |
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| [GGUF](https://huggingface.co/mradermacher/Qwen2.5-7B-Instruct-1M-Thinking-Claude-Gemini-GPT5.2-DISTILL-GGUF/resolve/main/Qwen2.5-7B-Instruct-1M-Thinking-Claude-Gemini-GPT5.2-DISTILL.IQ4_XS.gguf) | IQ4_XS | 4.4 | |
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| [GGUF](https://huggingface.co/mradermacher/Qwen2.5-7B-Instruct-1M-Thinking-Claude-Gemini-GPT5.2-DISTILL-GGUF/resolve/main/Qwen2.5-7B-Instruct-1M-Thinking-Claude-Gemini-GPT5.2-DISTILL.Q4_K_S.gguf) | Q4_K_S | 4.6 | fast, recommended |
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| [GGUF](https://huggingface.co/mradermacher/Qwen2.5-7B-Instruct-1M-Thinking-Claude-Gemini-GPT5.2-DISTILL-GGUF/resolve/main/Qwen2.5-7B-Instruct-1M-Thinking-Claude-Gemini-GPT5.2-DISTILL.Q4_K_M.gguf) | Q4_K_M | 4.8 | fast, recommended |
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| [GGUF](https://huggingface.co/mradermacher/Qwen2.5-7B-Instruct-1M-Thinking-Claude-Gemini-GPT5.2-DISTILL-GGUF/resolve/main/Qwen2.5-7B-Instruct-1M-Thinking-Claude-Gemini-GPT5.2-DISTILL.Q5_K_S.gguf) | Q5_K_S | 5.4 | |
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| [GGUF](https://huggingface.co/mradermacher/Qwen2.5-7B-Instruct-1M-Thinking-Claude-Gemini-GPT5.2-DISTILL-GGUF/resolve/main/Qwen2.5-7B-Instruct-1M-Thinking-Claude-Gemini-GPT5.2-DISTILL.Q5_K_M.gguf) | Q5_K_M | 5.5 | |
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| [GGUF](https://huggingface.co/mradermacher/Qwen2.5-7B-Instruct-1M-Thinking-Claude-Gemini-GPT5.2-DISTILL-GGUF/resolve/main/Qwen2.5-7B-Instruct-1M-Thinking-Claude-Gemini-GPT5.2-DISTILL.Q6_K.gguf) | Q6_K | 6.4 | very good quality |
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| [GGUF](https://huggingface.co/mradermacher/Qwen2.5-7B-Instruct-1M-Thinking-Claude-Gemini-GPT5.2-DISTILL-GGUF/resolve/main/Qwen2.5-7B-Instruct-1M-Thinking-Claude-Gemini-GPT5.2-DISTILL.Q8_0.gguf) | Q8_0 | 8.2 | fast, best quality |
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| [GGUF](https://huggingface.co/mradermacher/Qwen2.5-7B-Instruct-1M-Thinking-Claude-Gemini-GPT5.2-DISTILL-GGUF/resolve/main/Qwen2.5-7B-Instruct-1M-Thinking-Claude-Gemini-GPT5.2-DISTILL.f16.gguf) | f16 | 15.3 | 16 bpw, overkill |
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Here is a handy graph by ikawrakow comparing some lower-quality quant
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types (lower is better):
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And here are Artefact2's thoughts on the matter:
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https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9
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## FAQ / Model Request
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See https://huggingface.co/mradermacher/model_requests for some answers to
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questions you might have and/or if you want some other model quantized.
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## Thanks
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I thank my company, [nethype GmbH](https://www.nethype.de/), for letting
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me use its servers and providing upgrades to my workstation to enable
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this work in my free time.
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<!-- end -->
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