96 lines
4.4 KiB
Markdown
96 lines
4.4 KiB
Markdown
---
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base_model: NovaCorp/Shadowncensored-1B
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library_name: transformers
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tags:
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- mergekit
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- merge
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---
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# GGUF Files for Shadowncensored-1B
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These are the GGUF files for [NovaCorp/Shadowncensored-1B](https://huggingface.co/NovaCorp/Shadowncensored-1B).
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## Downloads
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| GGUF Link | Quantization | Description |
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| ---- | ----- | ----------- |
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| [Download](https://huggingface.co/Flexan/NovaCorp-Shadowncensored-1B-GGUF/resolve/main/Shadowncensored-1B.Q2_K.gguf) | Q2_K | Lowest quality |
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| [Download](https://huggingface.co/Flexan/NovaCorp-Shadowncensored-1B-GGUF/resolve/main/Shadowncensored-1B.Q3_K_S.gguf) | Q3_K_S | |
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| [Download](https://huggingface.co/Flexan/NovaCorp-Shadowncensored-1B-GGUF/resolve/main/Shadowncensored-1B.IQ3_S.gguf) | IQ3_S | Integer quant, preferable over Q3_K_S |
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| [Download](https://huggingface.co/Flexan/NovaCorp-Shadowncensored-1B-GGUF/resolve/main/Shadowncensored-1B.IQ3_M.gguf) | IQ3_M | Integer quant |
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| [Download](https://huggingface.co/Flexan/NovaCorp-Shadowncensored-1B-GGUF/resolve/main/Shadowncensored-1B.Q3_K_M.gguf) | Q3_K_M | |
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| [Download](https://huggingface.co/Flexan/NovaCorp-Shadowncensored-1B-GGUF/resolve/main/Shadowncensored-1B.Q3_K_L.gguf) | Q3_K_L | |
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| [Download](https://huggingface.co/Flexan/NovaCorp-Shadowncensored-1B-GGUF/resolve/main/Shadowncensored-1B.IQ4_XS.gguf) | IQ4_XS | Integer quant |
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| [Download](https://huggingface.co/Flexan/NovaCorp-Shadowncensored-1B-GGUF/resolve/main/Shadowncensored-1B.Q4_K_S.gguf) | Q4_K_S | Fast with good performance |
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| [Download](https://huggingface.co/Flexan/NovaCorp-Shadowncensored-1B-GGUF/resolve/main/Shadowncensored-1B.Q4_K_M.gguf) | Q4_K_M | **Recommended:** Perfect mix of speed and performance |
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| [Download](https://huggingface.co/Flexan/NovaCorp-Shadowncensored-1B-GGUF/resolve/main/Shadowncensored-1B.Q5_K_S.gguf) | Q5_K_S | |
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| [Download](https://huggingface.co/Flexan/NovaCorp-Shadowncensored-1B-GGUF/resolve/main/Shadowncensored-1B.Q5_K_M.gguf) | Q5_K_M | |
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| [Download](https://huggingface.co/Flexan/NovaCorp-Shadowncensored-1B-GGUF/resolve/main/Shadowncensored-1B.Q6_K.gguf) | Q6_K | Very good quality |
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| [Download](https://huggingface.co/Flexan/NovaCorp-Shadowncensored-1B-GGUF/resolve/main/Shadowncensored-1B.Q8_0.gguf) | Q8_0 | Best quality |
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| [Download](https://huggingface.co/Flexan/NovaCorp-Shadowncensored-1B-GGUF/resolve/main/Shadowncensored-1B.f16.gguf) | f16 | Full precision, don't bother; use a quant |
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## Note from Flexan
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I provide GGUFs and quantizations of publicly available models that do not have a GGUF equivalent available yet,
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usually for models **I deem interesting and wish to try out**.
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If there are some quants missing that you'd like me to add, you may request one in the community tab.
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If you want to request a public model to be converted, you can also request that in the community tab.
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If you have questions regarding this model, please refer to [the original model repo](https://huggingface.co/NovaCorp/Shadowncensored-1B).
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You can find more info about me and what I do [here](https://huggingface.co/Flexan/Flexan).
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# Shadowncensored-1B
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This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
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## Merge Details
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### Merge Method
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This model was merged using the [SLERP](https://en.wikipedia.org/wiki/Slerp) merge method.
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### Models Merged
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The following models were included in the merge:
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* [lunahr/gemma-3-1b-it-abliterated](https://huggingface.co/lunahr/gemma-3-1b-it-abliterated)
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* [Echo9Zulu/Shadows-Gemma-3-1B](https://huggingface.co/Echo9Zulu/Shadows-Gemma-3-1B)
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### Configuration
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The following YAML configuration was used to produce this model:
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```yaml
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# Umbrella Corporation Official Merge Protocol v3.2
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# Author: Dr. Novaciano
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# Objective: Test
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# PROJECT: Shadowncensored-3.2-1B
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models:
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- model: lunahr/gemma-3-1b-it-abliterated # Experimental viral strain neural imprint
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- model: Echo9Zulu/Shadows-Gemma-3-1B # Baseline cognitive template, "safe mode"
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merge_method: slerp # Spherical Linear Interpolation to preserve extreme viral traits smoothly
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base_model: lunahr/gemma-3-1b-it-abliterated # Anchor model for stable latent space
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dtype: bfloat16 # Memory-efficient precision, minimal loss in viral feature fidelity
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parameters:
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t: 0.45
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normalize: false
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rescale: true
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rescale_factor: 1.12
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memory_efficient: true
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low_cpu_mem_usage: true
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layer_range:
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- value: [4, 22]
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tie_word_embeddings: true
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tie_output_embeddings: true
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``` |