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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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  weighted/imatrix quants of https://huggingface.co/huihui-ai/Llama-3.3-70B-Instruct-abliterated
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ of the following means:\n* Reporting issues with the model: [https://github.com/meta-llama/llama-models/issues](https://l.workplace.com/l.php?u=https%3A%2F%2Fgithub.com%2Fmeta-llama%2Fllama-models%2Fissues&h=AT0qV8W9BFT6NwihiOHRuKYQM_UnkzN_NmHMy91OT55gkLpgi4kQupHUl0ssR4dQsIQ8n3tfd0vtkobvsEvt1l4Ic6GXI2EeuHV8N08OG2WnbAmm0FL4ObkazC6G_256vN0lN9DsykCvCqGZ)
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+ language:
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+ - en
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+ - fr
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+ - it
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+ - pt
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+ - hi
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+ - es
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+ - th
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+ - de
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+ library_name: transformers
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+ license: llama3.3
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+ quantized_by: mradermacher
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+ tags:
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+ - facebook
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+ - meta
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+ - pytorch
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+ - llama
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+ - llama-3
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+ - abliterated
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+ - uncensored
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+ ---
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+ ## About
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+
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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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  weighted/imatrix quants of https://huggingface.co/huihui-ai/Llama-3.3-70B-Instruct-abliterated
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+
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+ <!-- provided-files -->
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+ static quants are available at https://huggingface.co/mradermacher/Llama-3.3-70B-Instruct-abliterated-GGUF
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+ ## Usage
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+
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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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+
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+ ## Provided Quants
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+
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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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+
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+ | Link | Type | Size/GB | Notes |
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+ |:-----|:-----|--------:|:------|
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+ | [GGUF](https://huggingface.co/mradermacher/Llama-3.3-70B-Instruct-abliterated-i1-GGUF/resolve/main/Llama-3.3-70B-Instruct-abliterated.i1-IQ1_S.gguf) | i1-IQ1_S | 15.4 | for the desperate |
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+ | [GGUF](https://huggingface.co/mradermacher/Llama-3.3-70B-Instruct-abliterated-i1-GGUF/resolve/main/Llama-3.3-70B-Instruct-abliterated.i1-IQ1_M.gguf) | i1-IQ1_M | 16.9 | mostly desperate |
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+ | [GGUF](https://huggingface.co/mradermacher/Llama-3.3-70B-Instruct-abliterated-i1-GGUF/resolve/main/Llama-3.3-70B-Instruct-abliterated.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 19.2 | |
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+ | [GGUF](https://huggingface.co/mradermacher/Llama-3.3-70B-Instruct-abliterated-i1-GGUF/resolve/main/Llama-3.3-70B-Instruct-abliterated.i1-IQ2_XS.gguf) | i1-IQ2_XS | 21.2 | |
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+ | [GGUF](https://huggingface.co/mradermacher/Llama-3.3-70B-Instruct-abliterated-i1-GGUF/resolve/main/Llama-3.3-70B-Instruct-abliterated.i1-IQ2_S.gguf) | i1-IQ2_S | 22.3 | |
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+ | [GGUF](https://huggingface.co/mradermacher/Llama-3.3-70B-Instruct-abliterated-i1-GGUF/resolve/main/Llama-3.3-70B-Instruct-abliterated.i1-IQ2_M.gguf) | i1-IQ2_M | 24.2 | |
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+ | [GGUF](https://huggingface.co/mradermacher/Llama-3.3-70B-Instruct-abliterated-i1-GGUF/resolve/main/Llama-3.3-70B-Instruct-abliterated.i1-Q2_K_S.gguf) | i1-Q2_K_S | 24.6 | very low quality |
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+ | [GGUF](https://huggingface.co/mradermacher/Llama-3.3-70B-Instruct-abliterated-i1-GGUF/resolve/main/Llama-3.3-70B-Instruct-abliterated.i1-Q2_K.gguf) | i1-Q2_K | 26.5 | IQ3_XXS probably better |
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+ | [GGUF](https://huggingface.co/mradermacher/Llama-3.3-70B-Instruct-abliterated-i1-GGUF/resolve/main/Llama-3.3-70B-Instruct-abliterated.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 27.6 | lower quality |
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+ | [GGUF](https://huggingface.co/mradermacher/Llama-3.3-70B-Instruct-abliterated-i1-GGUF/resolve/main/Llama-3.3-70B-Instruct-abliterated.i1-IQ3_XS.gguf) | i1-IQ3_XS | 29.4 | |
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+ | [GGUF](https://huggingface.co/mradermacher/Llama-3.3-70B-Instruct-abliterated-i1-GGUF/resolve/main/Llama-3.3-70B-Instruct-abliterated.i1-IQ3_S.gguf) | i1-IQ3_S | 31.0 | beats Q3_K* |
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+ | [GGUF](https://huggingface.co/mradermacher/Llama-3.3-70B-Instruct-abliterated-i1-GGUF/resolve/main/Llama-3.3-70B-Instruct-abliterated.i1-Q3_K_S.gguf) | i1-Q3_K_S | 31.0 | IQ3_XS probably better |
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+ | [GGUF](https://huggingface.co/mradermacher/Llama-3.3-70B-Instruct-abliterated-i1-GGUF/resolve/main/Llama-3.3-70B-Instruct-abliterated.i1-IQ3_M.gguf) | i1-IQ3_M | 32.0 | |
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+ | [GGUF](https://huggingface.co/mradermacher/Llama-3.3-70B-Instruct-abliterated-i1-GGUF/resolve/main/Llama-3.3-70B-Instruct-abliterated.i1-Q3_K_M.gguf) | i1-Q3_K_M | 34.4 | IQ3_S probably better |
240
+ | [GGUF](https://huggingface.co/mradermacher/Llama-3.3-70B-Instruct-abliterated-i1-GGUF/resolve/main/Llama-3.3-70B-Instruct-abliterated.i1-Q3_K_L.gguf) | i1-Q3_K_L | 37.2 | IQ3_M probably better |
241
+ | [GGUF](https://huggingface.co/mradermacher/Llama-3.3-70B-Instruct-abliterated-i1-GGUF/resolve/main/Llama-3.3-70B-Instruct-abliterated.i1-IQ4_XS.gguf) | i1-IQ4_XS | 38.0 | |
242
+ | [GGUF](https://huggingface.co/mradermacher/Llama-3.3-70B-Instruct-abliterated-i1-GGUF/resolve/main/Llama-3.3-70B-Instruct-abliterated.i1-Q4_0.gguf) | i1-Q4_0 | 40.2 | fast, low quality |
243
+ | [GGUF](https://huggingface.co/mradermacher/Llama-3.3-70B-Instruct-abliterated-i1-GGUF/resolve/main/Llama-3.3-70B-Instruct-abliterated.i1-Q4_K_S.gguf) | i1-Q4_K_S | 40.4 | optimal size/speed/quality |
244
+ | [GGUF](https://huggingface.co/mradermacher/Llama-3.3-70B-Instruct-abliterated-i1-GGUF/resolve/main/Llama-3.3-70B-Instruct-abliterated.i1-Q4_K_M.gguf) | i1-Q4_K_M | 42.6 | fast, recommended |
245
+ | [GGUF](https://huggingface.co/mradermacher/Llama-3.3-70B-Instruct-abliterated-i1-GGUF/resolve/main/Llama-3.3-70B-Instruct-abliterated.i1-Q5_K_S.gguf) | i1-Q5_K_S | 48.8 | |
246
+ | [GGUF](https://huggingface.co/mradermacher/Llama-3.3-70B-Instruct-abliterated-i1-GGUF/resolve/main/Llama-3.3-70B-Instruct-abliterated.i1-Q5_K_M.gguf) | i1-Q5_K_M | 50.0 | |
247
+ | [PART 1](https://huggingface.co/mradermacher/Llama-3.3-70B-Instruct-abliterated-i1-GGUF/resolve/main/Llama-3.3-70B-Instruct-abliterated.i1-Q6_K.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/Llama-3.3-70B-Instruct-abliterated-i1-GGUF/resolve/main/Llama-3.3-70B-Instruct-abliterated.i1-Q6_K.gguf.part2of2) | i1-Q6_K | 58.0 | practically like static Q6_K |
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+
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+ Here is a handy graph by ikawrakow comparing some lower-quality quant
250
+ types (lower is better):
251
+
252
+ ![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.png)
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+
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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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+
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+ ## FAQ / Model Request
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+
259
+ See https://huggingface.co/mradermacher/model_requests for some answers to
260
+ questions you might have and/or if you want some other model quantized.
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+
262
+ ## Thanks
263
+
264
+ I thank my company, [nethype GmbH](https://www.nethype.de/), for letting
265
+ me use its servers and providing upgrades to my workstation to enable
266
+ 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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+
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+ <!-- end -->