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						base_model: ValiantLabs/Llama3.1-8B-Enigma | 
					
					
						
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						datasets: | 
					
					
						
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						- sequelbox/Tachibana | 
					
					
						
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						- sequelbox/Supernova | 
					
					
						
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						language: | 
					
					
						
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						- en | 
					
					
						
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						library_name: transformers | 
					
					
						
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						license: llama3.1 | 
					
					
						
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						model_type: llama | 
					
					
						
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						quantized_by: mradermacher | 
					
					
						
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						tags: | 
					
					
						
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						- enigma | 
					
					
						
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						- valiant | 
					
					
						
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						- valiant-labs | 
					
					
						
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						- llama | 
					
					
						
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						- llama-3.1 | 
					
					
						
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						- llama-3.1-instruct | 
					
					
						
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						- llama-3.1-instruct-8b | 
					
					
						
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						- llama-3 | 
					
					
						
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						- llama-3-instruct | 
					
					
						
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						- llama-3-instruct-8b | 
					
					
						
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						- 8b | 
					
					
						
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						- code | 
					
					
						
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						- code-instruct | 
					
					
						
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						- python | 
					
					
						
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						- conversational | 
					
					
						
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						- chat | 
					
					
						
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						- instruct | 
					
					
						
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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/ValiantLabs/Llama3.1-8B-Enigma | 
					
					
						
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						 | 
					
					
						
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						<!-- provided-files --> | 
					
					
						
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						weighted/imatrix quants are available at https://huggingface.co/mradermacher/Llama3.1-8B-Enigma-i1-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/Llama3.1-8B-Enigma-GGUF/resolve/main/Llama3.1-8B-Enigma.Q2_K.gguf) | Q2_K | 3.3 |  | | 
					
					
						
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						| [GGUF](https://huggingface.co/mradermacher/Llama3.1-8B-Enigma-GGUF/resolve/main/Llama3.1-8B-Enigma.Q3_K_S.gguf) | Q3_K_S | 3.8 |  | | 
					
					
						
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						| [GGUF](https://huggingface.co/mradermacher/Llama3.1-8B-Enigma-GGUF/resolve/main/Llama3.1-8B-Enigma.Q3_K_M.gguf) | Q3_K_M | 4.1 | lower quality | | 
					
					
						
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						| [GGUF](https://huggingface.co/mradermacher/Llama3.1-8B-Enigma-GGUF/resolve/main/Llama3.1-8B-Enigma.Q3_K_L.gguf) | Q3_K_L | 4.4 |  | | 
					
					
						
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						| [GGUF](https://huggingface.co/mradermacher/Llama3.1-8B-Enigma-GGUF/resolve/main/Llama3.1-8B-Enigma.IQ4_XS.gguf) | IQ4_XS | 4.6 |  | | 
					
					
						
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						| [GGUF](https://huggingface.co/mradermacher/Llama3.1-8B-Enigma-GGUF/resolve/main/Llama3.1-8B-Enigma.Q4_0_4_4.gguf) | Q4_0_4_4 | 4.8 | fast on arm, low quality | | 
					
					
						
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						| [GGUF](https://huggingface.co/mradermacher/Llama3.1-8B-Enigma-GGUF/resolve/main/Llama3.1-8B-Enigma.Q4_K_S.gguf) | Q4_K_S | 4.8 | fast, recommended | | 
					
					
						
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						| [GGUF](https://huggingface.co/mradermacher/Llama3.1-8B-Enigma-GGUF/resolve/main/Llama3.1-8B-Enigma.Q4_K_M.gguf) | Q4_K_M | 5.0 | fast, recommended | | 
					
					
						
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						| [GGUF](https://huggingface.co/mradermacher/Llama3.1-8B-Enigma-GGUF/resolve/main/Llama3.1-8B-Enigma.Q5_K_S.gguf) | Q5_K_S | 5.7 |  | | 
					
					
						
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						| [GGUF](https://huggingface.co/mradermacher/Llama3.1-8B-Enigma-GGUF/resolve/main/Llama3.1-8B-Enigma.Q5_K_M.gguf) | Q5_K_M | 5.8 |  | | 
					
					
						
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						| [GGUF](https://huggingface.co/mradermacher/Llama3.1-8B-Enigma-GGUF/resolve/main/Llama3.1-8B-Enigma.Q6_K.gguf) | Q6_K | 6.7 | very good quality | | 
					
					
						
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						| [GGUF](https://huggingface.co/mradermacher/Llama3.1-8B-Enigma-GGUF/resolve/main/Llama3.1-8B-Enigma.Q8_0.gguf) | Q8_0 | 8.6 | fast, best quality | | 
					
					
						
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						| [GGUF](https://huggingface.co/mradermacher/Llama3.1-8B-Enigma-GGUF/resolve/main/Llama3.1-8B-Enigma.f16.gguf) | f16 | 16.2 | 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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 | 
					
					
						
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						 | 
					
					
						
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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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						## 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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						 | 
					
					
						
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						## Thanks | 
					
					
						
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						 | 
					
					
						
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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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						 | 
					
					
						
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						<!-- end --> | 
					
					
						
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