206 lines
6.8 KiB
Markdown
206 lines
6.8 KiB
Markdown
---
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base_model: thelamapi/next-12b
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datasets:
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- mlabonne/FineTome-100k
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- ITCL/FineTomeOs
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- Gryphe/ChatGPT-4o-Writing-Prompts
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- dongguanting/ARPO-SFT-54K
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- GreenerPastures/All-Your-Base-Full
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- Gryphe/Opus-WritingPrompts
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- HuggingFaceH4/MATH-500
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- mlabonne/smoltalk-flat
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- mlabonne/natural_reasoning-formatted
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- OpenSPG/KAG-Thinker-training-dataset
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- uclanlp/Brief-Pro
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- CognitiveKernel/CognitiveKernel-Pro-SFT
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- SuperbEmphasis/Claude-4.0-DeepSeek-R1-RP-SFWish
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- QuixiAI/dolphin-r1
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- mlabonne/lmsys-arena-human-sft-55k
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language:
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- tr
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- en
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- de
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- ka
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- el
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- ku
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- es
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- sl
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- sk
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- af
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- da
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- nl
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- fa
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- fi
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- fr
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- ga
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- hi
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- hu
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- hy
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- ja
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- kg
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- kk
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- ko
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- ky
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- la
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- lb
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- id
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- it
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- is
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- za
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- zh
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- zu
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- cs
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- vi
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- be
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- bg
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- bs
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- ne
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- mn
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- rm
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- ro
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- ru
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- te
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- th
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- tk
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- tt
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- uk
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- uz
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- ug
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- pl
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- pt
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- no
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library_name: transformers
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license: mit
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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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- turkish
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- türkiye
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- english
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- ai
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- lamapi
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- gemma3
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- next
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- next-x1
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- efficient
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- text-generation
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- open-source
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- 12b
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- huggingface
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- large-language-model
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- llm
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- causal
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- transformer
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- artificial-intelligence
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- machine-learning
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- ai-research
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- natural-language-processing
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- language
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- multilingual
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- multimodal
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- nlp
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- finetuned
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- lightweight
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- creative
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- summarization
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- question-answering
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- chat
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- generative-ai
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- optimized
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- unsloth
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- trl
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- sft
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- chemistry
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- code
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- biology
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- finance
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- legal
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- music
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- art
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- state-of-the-art
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- climate
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- medical
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- agent
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- text-generation-inference
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- merge
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- dense
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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: nicoboss -->
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<!-- ### quants: Q2_K IQ3_M Q4_K_S IQ3_XXS Q3_K_M small-IQ4_NL Q4_K_M IQ2_M Q6_K IQ4_XS Q2_K_S IQ1_M Q3_K_S IQ2_XXS Q3_K_L IQ2_XS Q5_K_S IQ2_S IQ1_S Q5_K_M Q4_0 IQ3_XS Q4_1 IQ3_S -->
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<!-- ### quants_skip: -->
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<!-- ### skip_mmproj: -->
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weighted/imatrix quants of https://huggingface.co/thelamapi/next-12b
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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#next-12b-i1-GGUF).***
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static quants are available at https://huggingface.co/mradermacher/next-12b-GGUF
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**This is a vision model - mmproj files (if any) will be in the [static repository](https://huggingface.co/mradermacher/next-12b-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/next-12b-i1-GGUF/resolve/main/next-12b.imatrix.gguf) | imatrix | 0.1 | imatrix file (for creating your own quants) |
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| [GGUF](https://huggingface.co/mradermacher/next-12b-i1-GGUF/resolve/main/next-12b.i1-IQ1_S.gguf) | i1-IQ1_S | 3.0 | for the desperate |
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| [GGUF](https://huggingface.co/mradermacher/next-12b-i1-GGUF/resolve/main/next-12b.i1-IQ1_M.gguf) | i1-IQ1_M | 3.3 | mostly desperate |
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| [GGUF](https://huggingface.co/mradermacher/next-12b-i1-GGUF/resolve/main/next-12b.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 3.6 | |
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| [GGUF](https://huggingface.co/mradermacher/next-12b-i1-GGUF/resolve/main/next-12b.i1-IQ2_XS.gguf) | i1-IQ2_XS | 3.9 | |
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| [GGUF](https://huggingface.co/mradermacher/next-12b-i1-GGUF/resolve/main/next-12b.i1-IQ2_S.gguf) | i1-IQ2_S | 4.1 | |
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| [GGUF](https://huggingface.co/mradermacher/next-12b-i1-GGUF/resolve/main/next-12b.i1-IQ2_M.gguf) | i1-IQ2_M | 4.4 | |
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| [GGUF](https://huggingface.co/mradermacher/next-12b-i1-GGUF/resolve/main/next-12b.i1-Q2_K_S.gguf) | i1-Q2_K_S | 4.5 | very low quality |
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| [GGUF](https://huggingface.co/mradermacher/next-12b-i1-GGUF/resolve/main/next-12b.i1-Q2_K.gguf) | i1-Q2_K | 4.9 | IQ3_XXS probably better |
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| [GGUF](https://huggingface.co/mradermacher/next-12b-i1-GGUF/resolve/main/next-12b.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 4.9 | lower quality |
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| [GGUF](https://huggingface.co/mradermacher/next-12b-i1-GGUF/resolve/main/next-12b.i1-IQ3_XS.gguf) | i1-IQ3_XS | 5.3 | |
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| [GGUF](https://huggingface.co/mradermacher/next-12b-i1-GGUF/resolve/main/next-12b.i1-IQ3_S.gguf) | i1-IQ3_S | 5.6 | beats Q3_K* |
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| [GGUF](https://huggingface.co/mradermacher/next-12b-i1-GGUF/resolve/main/next-12b.i1-Q3_K_S.gguf) | i1-Q3_K_S | 5.6 | IQ3_XS probably better |
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| [GGUF](https://huggingface.co/mradermacher/next-12b-i1-GGUF/resolve/main/next-12b.i1-IQ3_M.gguf) | i1-IQ3_M | 5.8 | |
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| [GGUF](https://huggingface.co/mradermacher/next-12b-i1-GGUF/resolve/main/next-12b.i1-Q3_K_M.gguf) | i1-Q3_K_M | 6.1 | IQ3_S probably better |
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| [GGUF](https://huggingface.co/mradermacher/next-12b-i1-GGUF/resolve/main/next-12b.i1-Q3_K_L.gguf) | i1-Q3_K_L | 6.6 | IQ3_M probably better |
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| [GGUF](https://huggingface.co/mradermacher/next-12b-i1-GGUF/resolve/main/next-12b.i1-IQ4_XS.gguf) | i1-IQ4_XS | 6.7 | |
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| [GGUF](https://huggingface.co/mradermacher/next-12b-i1-GGUF/resolve/main/next-12b.i1-IQ4_NL.gguf) | i1-IQ4_NL | 7.0 | prefer IQ4_XS |
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| [GGUF](https://huggingface.co/mradermacher/next-12b-i1-GGUF/resolve/main/next-12b.i1-Q4_0.gguf) | i1-Q4_0 | 7.0 | fast, low quality |
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| [GGUF](https://huggingface.co/mradermacher/next-12b-i1-GGUF/resolve/main/next-12b.i1-Q4_K_S.gguf) | i1-Q4_K_S | 7.0 | optimal size/speed/quality |
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| [GGUF](https://huggingface.co/mradermacher/next-12b-i1-GGUF/resolve/main/next-12b.i1-Q4_K_M.gguf) | i1-Q4_K_M | 7.4 | fast, recommended |
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| [GGUF](https://huggingface.co/mradermacher/next-12b-i1-GGUF/resolve/main/next-12b.i1-Q4_1.gguf) | i1-Q4_1 | 7.7 | |
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| [GGUF](https://huggingface.co/mradermacher/next-12b-i1-GGUF/resolve/main/next-12b.i1-Q5_K_S.gguf) | i1-Q5_K_S | 8.3 | |
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| [GGUF](https://huggingface.co/mradermacher/next-12b-i1-GGUF/resolve/main/next-12b.i1-Q5_K_M.gguf) | i1-Q5_K_M | 8.5 | |
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| [GGUF](https://huggingface.co/mradermacher/next-12b-i1-GGUF/resolve/main/next-12b.i1-Q6_K.gguf) | i1-Q6_K | 9.8 | practically like static Q6_K |
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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. Additional thanks to [@nicoboss](https://huggingface.co/nicoboss) for giving me access to his private supercomputer, enabling me to provide many more imatrix quants, at much higher quality, than I would otherwise be able to.
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