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Model: mradermacher/Rawr_Llama3_8B-i1-GGUF Source: Original Platform
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Rawr_Llama3_8B.i1-Q2_K.gguf filter=lfs diff=lfs merge=lfs -text
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README.md
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---
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base_model: ResplendentAI/Rawr_Llama3_8B
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language:
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- en
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library_name: transformers
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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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---
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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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weighted/imatrix quants of https://huggingface.co/ResplendentAI/Rawr_Llama3_8B
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<!-- provided-files -->
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static quants are available at https://huggingface.co/mradermacher/Rawr_Llama3_8B-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/Rawr_Llama3_8B-i1-GGUF/resolve/main/Rawr_Llama3_8B.i1-IQ1_S.gguf) | i1-IQ1_S | 2.1 | for the desperate |
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| [GGUF](https://huggingface.co/mradermacher/Rawr_Llama3_8B-i1-GGUF/resolve/main/Rawr_Llama3_8B.i1-IQ1_M.gguf) | i1-IQ1_M | 2.3 | mostly desperate |
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| [GGUF](https://huggingface.co/mradermacher/Rawr_Llama3_8B-i1-GGUF/resolve/main/Rawr_Llama3_8B.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 2.5 | |
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| [GGUF](https://huggingface.co/mradermacher/Rawr_Llama3_8B-i1-GGUF/resolve/main/Rawr_Llama3_8B.i1-IQ2_XS.gguf) | i1-IQ2_XS | 2.7 | |
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| [GGUF](https://huggingface.co/mradermacher/Rawr_Llama3_8B-i1-GGUF/resolve/main/Rawr_Llama3_8B.i1-IQ2_S.gguf) | i1-IQ2_S | 2.9 | |
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| [GGUF](https://huggingface.co/mradermacher/Rawr_Llama3_8B-i1-GGUF/resolve/main/Rawr_Llama3_8B.i1-IQ2_M.gguf) | i1-IQ2_M | 3.0 | |
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| [GGUF](https://huggingface.co/mradermacher/Rawr_Llama3_8B-i1-GGUF/resolve/main/Rawr_Llama3_8B.i1-Q2_K.gguf) | i1-Q2_K | 3.3 | IQ3_XXS probably better |
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| [GGUF](https://huggingface.co/mradermacher/Rawr_Llama3_8B-i1-GGUF/resolve/main/Rawr_Llama3_8B.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 3.4 | lower quality |
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| [GGUF](https://huggingface.co/mradermacher/Rawr_Llama3_8B-i1-GGUF/resolve/main/Rawr_Llama3_8B.i1-IQ3_XS.gguf) | i1-IQ3_XS | 3.6 | |
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| [GGUF](https://huggingface.co/mradermacher/Rawr_Llama3_8B-i1-GGUF/resolve/main/Rawr_Llama3_8B.i1-Q3_K_S.gguf) | i1-Q3_K_S | 3.8 | IQ3_XS probably better |
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| [GGUF](https://huggingface.co/mradermacher/Rawr_Llama3_8B-i1-GGUF/resolve/main/Rawr_Llama3_8B.i1-IQ3_S.gguf) | i1-IQ3_S | 3.8 | beats Q3_K* |
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| [GGUF](https://huggingface.co/mradermacher/Rawr_Llama3_8B-i1-GGUF/resolve/main/Rawr_Llama3_8B.i1-IQ3_M.gguf) | i1-IQ3_M | 3.9 | |
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| [GGUF](https://huggingface.co/mradermacher/Rawr_Llama3_8B-i1-GGUF/resolve/main/Rawr_Llama3_8B.i1-Q3_K_M.gguf) | i1-Q3_K_M | 4.1 | IQ3_S probably better |
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| [GGUF](https://huggingface.co/mradermacher/Rawr_Llama3_8B-i1-GGUF/resolve/main/Rawr_Llama3_8B.i1-Q3_K_L.gguf) | i1-Q3_K_L | 4.4 | IQ3_M probably better |
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| [GGUF](https://huggingface.co/mradermacher/Rawr_Llama3_8B-i1-GGUF/resolve/main/Rawr_Llama3_8B.i1-IQ4_XS.gguf) | i1-IQ4_XS | 4.5 | |
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| [GGUF](https://huggingface.co/mradermacher/Rawr_Llama3_8B-i1-GGUF/resolve/main/Rawr_Llama3_8B.i1-Q4_0.gguf) | i1-Q4_0 | 4.8 | fast, low quality |
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| [GGUF](https://huggingface.co/mradermacher/Rawr_Llama3_8B-i1-GGUF/resolve/main/Rawr_Llama3_8B.i1-Q4_K_S.gguf) | i1-Q4_K_S | 4.8 | optimal size/speed/quality |
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| [GGUF](https://huggingface.co/mradermacher/Rawr_Llama3_8B-i1-GGUF/resolve/main/Rawr_Llama3_8B.i1-Q4_K_M.gguf) | i1-Q4_K_M | 5.0 | fast, recommended |
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| [GGUF](https://huggingface.co/mradermacher/Rawr_Llama3_8B-i1-GGUF/resolve/main/Rawr_Llama3_8B.i1-Q5_K_S.gguf) | i1-Q5_K_S | 5.7 | |
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| [GGUF](https://huggingface.co/mradermacher/Rawr_Llama3_8B-i1-GGUF/resolve/main/Rawr_Llama3_8B.i1-Q5_K_M.gguf) | i1-Q5_K_M | 5.8 | |
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| [GGUF](https://huggingface.co/mradermacher/Rawr_Llama3_8B-i1-GGUF/resolve/main/Rawr_Llama3_8B.i1-Q6_K.gguf) | i1-Q6_K | 6.7 | 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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<!-- end -->
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||||
oid sha256:2b43f31369667621dde41e8b2e2197362008bbf3d5dcc73dd4f17f14cbe642a2
|
||||
size 5599294400
|
||||
3
Rawr_Llama3_8B.i1-Q6_K.gguf
Normal file
3
Rawr_Llama3_8B.i1-Q6_K.gguf
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:faf8e35df425b8af6076cc46070429cb46a47e8913f2e2657ea4a7bf03007d39
|
||||
size 6596006848
|
||||
3
imatrix.dat
Normal file
3
imatrix.dat
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:a9b68e27ec1d6deea1f8b30f7b8d73daad5f92ee9930892d8b8ca071568b7f41
|
||||
size 4988143
|
||||
Reference in New Issue
Block a user