126 lines
5.2 KiB
Markdown
126 lines
5.2 KiB
Markdown
---
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base_model: Novaciano/RUN-WITH-SCISSORS-3.2-1B
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datasets:
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- HuggingFaceTB/smoltalk
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- Guilherme34/uncensor
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- teknium/OpenHermes-2.5
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- passing2961/multifaceted-skill-of-mind
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- PawanKrd/math-gpt-4o-200k
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- V3N0M/Jenna-50K-Alpaca-Uncensored
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- cognitivecomputations/dolphin-coder
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- mlabonne/FineTome-100k
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- microsoft/orca-math-word-problems-200k
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- CarrotAI/ko-instruction-dataset
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- Salesforce/xlam-function-calling-60k
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- anthracite-org/kalo-opus-instruct-22k-no-refusal
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- anthracite-org/stheno-filtered-v1.1
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- anthracite-org/nopm_claude_writing_fixed
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- AiAF/SCPWiki-Archive-02-March-2025-Datasets
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- huihui-ai/QWQ-LONGCOT-500K
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- huihui-ai/LONGCOT-Refine-500K
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- Epiculous/Synthstruct-Gens-v1.1-Filtered-n-Cleaned
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- Epiculous/SynthRP-Gens-v1.1-Filtered-n-Cleaned
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- alexandreteles/AlpacaToxicQA_ShareGPT
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- Nitral-AI/Active_RP-ShareGPT
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- PJMixers/hieunguyenminh_roleplay-deduped-ShareGPT
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- Nitral-AI/RP_Alignment-ShareGPT
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- Chaser-cz/sonnet35-charcard-roleplay-sharegpt
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- AiCloser/sharegpt_cot_dataset
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- PJMixers/Gryphe_Opus-WritingPrompts-Story2Prompt-ShareGPT
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- priveeai/pippa_sharegpt
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- Locutusque/sharegpt_gpt4_uncensored_cleaned
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- OpenCoder-LLM/opc-sft-stage1
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- OpenCoder-LLM/opc-sft-stage2
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- microsoft/orca-agentinstruct-1M-v1
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- NousResearch/hermes-function-calling-v1
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- AI-MO/NuminaMath-CoT
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- AI-MO/NuminaMath-TIR
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- allenai/tulu-3-sft-mixture
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- cognitivecomputations/samantha-data
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- m-a-p/CodeFeedback-Filtered-Instruction
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- m-a-p/Code-Feedback
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- FreedomIntelligence/medical-o1-reasoning-SFT
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language:
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- en
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- es
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library_name: transformers
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license: llama3
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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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- mergekit
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- merge
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- nsfw
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- uncensored
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- abliterated
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- llama3
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- llama3.2
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- rp
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- roleplay
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- sillytavern
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- koboldcpp
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- 1b
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- 4-bit
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- not-for-all-audiences
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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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static quants of https://huggingface.co/Novaciano/RUN-WITH-SCISSORS-3.2-1B
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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#RUN-WITH-SCISSORS-3.2-1B-GGUF).***
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weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.
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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/RUN-WITH-SCISSORS-3.2-1B-GGUF/resolve/main/RUN-WITH-SCISSORS-3.2-1B.Q2_K.gguf) | Q2_K | 0.8 | |
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| [GGUF](https://huggingface.co/mradermacher/RUN-WITH-SCISSORS-3.2-1B-GGUF/resolve/main/RUN-WITH-SCISSORS-3.2-1B.Q3_K_S.gguf) | Q3_K_S | 0.9 | |
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| [GGUF](https://huggingface.co/mradermacher/RUN-WITH-SCISSORS-3.2-1B-GGUF/resolve/main/RUN-WITH-SCISSORS-3.2-1B.Q3_K_M.gguf) | Q3_K_M | 0.9 | lower quality |
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| [GGUF](https://huggingface.co/mradermacher/RUN-WITH-SCISSORS-3.2-1B-GGUF/resolve/main/RUN-WITH-SCISSORS-3.2-1B.Q3_K_L.gguf) | Q3_K_L | 0.9 | |
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| [GGUF](https://huggingface.co/mradermacher/RUN-WITH-SCISSORS-3.2-1B-GGUF/resolve/main/RUN-WITH-SCISSORS-3.2-1B.IQ4_XS.gguf) | IQ4_XS | 1.0 | |
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| [GGUF](https://huggingface.co/mradermacher/RUN-WITH-SCISSORS-3.2-1B-GGUF/resolve/main/RUN-WITH-SCISSORS-3.2-1B.Q4_K_S.gguf) | Q4_K_S | 1.0 | fast, recommended |
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| [GGUF](https://huggingface.co/mradermacher/RUN-WITH-SCISSORS-3.2-1B-GGUF/resolve/main/RUN-WITH-SCISSORS-3.2-1B.Q4_K_M.gguf) | Q4_K_M | 1.1 | fast, recommended |
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| [GGUF](https://huggingface.co/mradermacher/RUN-WITH-SCISSORS-3.2-1B-GGUF/resolve/main/RUN-WITH-SCISSORS-3.2-1B.Q5_K_S.gguf) | Q5_K_S | 1.2 | |
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| [GGUF](https://huggingface.co/mradermacher/RUN-WITH-SCISSORS-3.2-1B-GGUF/resolve/main/RUN-WITH-SCISSORS-3.2-1B.Q5_K_M.gguf) | Q5_K_M | 1.2 | |
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| [GGUF](https://huggingface.co/mradermacher/RUN-WITH-SCISSORS-3.2-1B-GGUF/resolve/main/RUN-WITH-SCISSORS-3.2-1B.Q6_K.gguf) | Q6_K | 1.3 | very good quality |
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| [GGUF](https://huggingface.co/mradermacher/RUN-WITH-SCISSORS-3.2-1B-GGUF/resolve/main/RUN-WITH-SCISSORS-3.2-1B.Q8_0.gguf) | Q8_0 | 1.7 | fast, best quality |
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| [GGUF](https://huggingface.co/mradermacher/RUN-WITH-SCISSORS-3.2-1B-GGUF/resolve/main/RUN-WITH-SCISSORS-3.2-1B.f16.gguf) | f16 | 3.1 | 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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