--- base_model: Lamapi/next-12b datasets: - mlabonne/FineTome-100k - ITCL/FineTomeOs - Gryphe/ChatGPT-4o-Writing-Prompts - dongguanting/ARPO-SFT-54K - GreenerPastures/All-Your-Base-Full - Gryphe/Opus-WritingPrompts - HuggingFaceH4/MATH-500 - mlabonne/smoltalk-flat - mlabonne/natural_reasoning-formatted - OpenSPG/KAG-Thinker-training-dataset - uclanlp/Brief-Pro - CognitiveKernel/CognitiveKernel-Pro-SFT - SuperbEmphasis/Claude-4.0-DeepSeek-R1-RP-SFWish - QuixiAI/dolphin-r1 - mlabonne/lmsys-arena-human-sft-55k language: - tr - en - de - ka - el - ku - es - sl - sk - af - da - nl - fa - fi - fr - ga - hi - hu - hy - ja - kg - kk - ko - ky - la - lb - id - it - is - za - zh - zu - cs - vi - be - bg - bs - ne - mn - rm - ro - ru - te - th - tk - tt - uk - uz - ug - pl - pt - no library_name: transformers license: mit mradermacher: readme_rev: 1 quantized_by: mradermacher tags: - turkish - türkiye - english - ai - lamapi - gemma3 - next - next-x1 - efficient - text-generation - open-source - 12b - huggingface - large-language-model - llm - causal - transformer - artificial-intelligence - machine-learning - ai-research - natural-language-processing - language - multilingual - multimodal - nlp - finetuned - lightweight - creative - summarization - question-answering - chat - generative-ai - optimized - unsloth - trl - sft - chemistry - code - biology - finance - legal - music - art - state-of-the-art - climate - medical - agent - text-generation-inference - merge - dense --- ## About static quants of https://huggingface.co/Lamapi/next-12b ***For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#next-12b-GGUF).*** weighted/imatrix quants are available at https://huggingface.co/mradermacher/next-12b-i1-GGUF ## Usage If you are unsure how to use GGUF files, refer to one of [TheBloke's READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for more details, including on how to concatenate multi-part files. ## Provided Quants (sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants) | Link | Type | Size/GB | Notes | |:-----|:-----|--------:|:------| | [GGUF](https://huggingface.co/mradermacher/next-12b-GGUF/resolve/main/next-12b.mmproj-Q8_0.gguf) | mmproj-Q8_0 | 0.7 | multi-modal supplement | | [GGUF](https://huggingface.co/mradermacher/next-12b-GGUF/resolve/main/next-12b.mmproj-f16.gguf) | mmproj-f16 | 1.0 | multi-modal supplement | | [GGUF](https://huggingface.co/mradermacher/next-12b-GGUF/resolve/main/next-12b.Q2_K.gguf) | Q2_K | 4.9 | | | [GGUF](https://huggingface.co/mradermacher/next-12b-GGUF/resolve/main/next-12b.Q3_K_S.gguf) | Q3_K_S | 5.6 | | | [GGUF](https://huggingface.co/mradermacher/next-12b-GGUF/resolve/main/next-12b.Q3_K_M.gguf) | Q3_K_M | 6.1 | lower quality | | [GGUF](https://huggingface.co/mradermacher/next-12b-GGUF/resolve/main/next-12b.Q3_K_L.gguf) | Q3_K_L | 6.6 | | | [GGUF](https://huggingface.co/mradermacher/next-12b-GGUF/resolve/main/next-12b.IQ4_XS.gguf) | IQ4_XS | 6.7 | | | [GGUF](https://huggingface.co/mradermacher/next-12b-GGUF/resolve/main/next-12b.Q4_K_S.gguf) | Q4_K_S | 7.0 | fast, recommended | | [GGUF](https://huggingface.co/mradermacher/next-12b-GGUF/resolve/main/next-12b.Q4_K_M.gguf) | Q4_K_M | 7.4 | fast, recommended | | [GGUF](https://huggingface.co/mradermacher/next-12b-GGUF/resolve/main/next-12b.Q5_K_S.gguf) | Q5_K_S | 8.3 | | | [GGUF](https://huggingface.co/mradermacher/next-12b-GGUF/resolve/main/next-12b.Q5_K_M.gguf) | Q5_K_M | 8.5 | | | [GGUF](https://huggingface.co/mradermacher/next-12b-GGUF/resolve/main/next-12b.Q6_K.gguf) | Q6_K | 9.8 | very good quality | | [GGUF](https://huggingface.co/mradermacher/next-12b-GGUF/resolve/main/next-12b.Q8_0.gguf) | Q8_0 | 12.6 | fast, best quality | Here is a handy graph by ikawrakow comparing some lower-quality quant types (lower is better): ![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.png) And here are Artefact2's thoughts on the matter: https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9 ## FAQ / Model Request See https://huggingface.co/mradermacher/model_requests for some answers to questions you might have and/or if you want some other model quantized. ## Thanks I thank my company, [nethype GmbH](https://www.nethype.de/), for letting me use its servers and providing upgrades to my workstation to enable this work in my free time.