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README.md

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+---
+base_model: Replete-AI/Llama3-8B-Instruct-Replete-Adapted
+datasets:
+- Replete-AI/code_bagel_hermes-2.5
+- Replete-AI/code_bagel
+- Replete-AI/OpenHermes-2.5-Uncensored
+- teknium/OpenHermes-2.5
+- layoric/tiny-codes-alpaca
+- glaiveai/glaive-code-assistant-v3
+- ajibawa-2023/Code-290k-ShareGPT
+- TIGER-Lab/MathInstruct
+- chargoddard/commitpack-ft-instruct-rated
+- iamturun/code_instructions_120k_alpaca
+- ise-uiuc/Magicoder-Evol-Instruct-110K
+- cognitivecomputations/dolphin-coder
+- nickrosh/Evol-Instruct-Code-80k-v1
+- coseal/CodeUltraFeedback_binarized
+- glaiveai/glaive-function-calling-v2
+- CyberNative/Code_Vulnerability_Security_DPO
+- jondurbin/airoboros-2.2
+- camel-ai
+- lmsys/lmsys-chat-1m
+- CollectiveCognition/chats-data-2023-09-22
+- CoT-Alpaca-GPT4
+- WizardLM/WizardLM_evol_instruct_70k
+- WizardLM/WizardLM_evol_instruct_V2_196k
+- teknium/GPT4-LLM-Cleaned
+- GPTeacher
+- OpenGPT
+- meta-math/MetaMathQA
+- Open-Orca/SlimOrca
+- garage-bAInd/Open-Platypus
+- anon8231489123/ShareGPT_Vicuna_unfiltered
+- Unnatural-Instructions-GPT4
+language:
+- en
+library_name: transformers
+license: other
+license_link: https://llama.meta.com/llama3/license/
+license_name: llama-3
+quantized_by: mradermacher
+tags:
+- text-generation-inference
+- transformers
+- unsloth
+- llama
+---
+## About
+
 <!-- ### quantize_version: 2 -->
 <!-- ### output_tensor_quantised: 1 -->
 <!-- ### convert_type: hf -->
 <!-- ### vocab_type:  -->
 <!-- ### tags: nicoboss -->
 weighted/imatrix quants of https://huggingface.co/Replete-AI/Llama3-8B-Instruct-Replete-Adapted
+
+<!-- provided-files -->
+static quants are available at https://huggingface.co/mradermacher/Llama3-8B-Instruct-Replete-Adapted-GGUF
+## Usage
+
+If you are unsure how to use GGUF files, refer to one of [TheBloke's
+READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for
+more details, including on how to concatenate multi-part files.
+
+## Provided Quants
+
+(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)
+
+| Link | Type | Size/GB | Notes |
+|:-----|:-----|--------:|:------|
+| [GGUF](https://huggingface.co/mradermacher/Llama3-8B-Instruct-Replete-Adapted-i1-GGUF/resolve/main/Llama3-8B-Instruct-Replete-Adapted.i1-IQ1_S.gguf) | i1-IQ1_S | 2.1 | for the desperate |
+| [GGUF](https://huggingface.co/mradermacher/Llama3-8B-Instruct-Replete-Adapted-i1-GGUF/resolve/main/Llama3-8B-Instruct-Replete-Adapted.i1-IQ1_M.gguf) | i1-IQ1_M | 2.3 | mostly desperate |
+| [GGUF](https://huggingface.co/mradermacher/Llama3-8B-Instruct-Replete-Adapted-i1-GGUF/resolve/main/Llama3-8B-Instruct-Replete-Adapted.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 2.5 |  |
+| [GGUF](https://huggingface.co/mradermacher/Llama3-8B-Instruct-Replete-Adapted-i1-GGUF/resolve/main/Llama3-8B-Instruct-Replete-Adapted.i1-IQ2_XS.gguf) | i1-IQ2_XS | 2.7 |  |
+| [GGUF](https://huggingface.co/mradermacher/Llama3-8B-Instruct-Replete-Adapted-i1-GGUF/resolve/main/Llama3-8B-Instruct-Replete-Adapted.i1-IQ2_S.gguf) | i1-IQ2_S | 2.9 |  |
+| [GGUF](https://huggingface.co/mradermacher/Llama3-8B-Instruct-Replete-Adapted-i1-GGUF/resolve/main/Llama3-8B-Instruct-Replete-Adapted.i1-IQ2_M.gguf) | i1-IQ2_M | 3.0 |  |
+| [GGUF](https://huggingface.co/mradermacher/Llama3-8B-Instruct-Replete-Adapted-i1-GGUF/resolve/main/Llama3-8B-Instruct-Replete-Adapted.i1-Q2_K.gguf) | i1-Q2_K | 3.3 | IQ3_XXS probably better |
+| [GGUF](https://huggingface.co/mradermacher/Llama3-8B-Instruct-Replete-Adapted-i1-GGUF/resolve/main/Llama3-8B-Instruct-Replete-Adapted.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 3.4 | lower quality |
+| [GGUF](https://huggingface.co/mradermacher/Llama3-8B-Instruct-Replete-Adapted-i1-GGUF/resolve/main/Llama3-8B-Instruct-Replete-Adapted.i1-IQ3_XS.gguf) | i1-IQ3_XS | 3.6 |  |
+| [GGUF](https://huggingface.co/mradermacher/Llama3-8B-Instruct-Replete-Adapted-i1-GGUF/resolve/main/Llama3-8B-Instruct-Replete-Adapted.i1-Q3_K_S.gguf) | i1-Q3_K_S | 3.8 | IQ3_XS probably better |
+| [GGUF](https://huggingface.co/mradermacher/Llama3-8B-Instruct-Replete-Adapted-i1-GGUF/resolve/main/Llama3-8B-Instruct-Replete-Adapted.i1-IQ3_S.gguf) | i1-IQ3_S | 3.8 | beats Q3_K* |
+| [GGUF](https://huggingface.co/mradermacher/Llama3-8B-Instruct-Replete-Adapted-i1-GGUF/resolve/main/Llama3-8B-Instruct-Replete-Adapted.i1-IQ3_M.gguf) | i1-IQ3_M | 3.9 |  |
+| [GGUF](https://huggingface.co/mradermacher/Llama3-8B-Instruct-Replete-Adapted-i1-GGUF/resolve/main/Llama3-8B-Instruct-Replete-Adapted.i1-Q3_K_M.gguf) | i1-Q3_K_M | 4.1 | IQ3_S probably better |
+| [GGUF](https://huggingface.co/mradermacher/Llama3-8B-Instruct-Replete-Adapted-i1-GGUF/resolve/main/Llama3-8B-Instruct-Replete-Adapted.i1-Q3_K_L.gguf) | i1-Q3_K_L | 4.4 | IQ3_M probably better |
+| [GGUF](https://huggingface.co/mradermacher/Llama3-8B-Instruct-Replete-Adapted-i1-GGUF/resolve/main/Llama3-8B-Instruct-Replete-Adapted.i1-IQ4_XS.gguf) | i1-IQ4_XS | 4.5 |  |
+| [GGUF](https://huggingface.co/mradermacher/Llama3-8B-Instruct-Replete-Adapted-i1-GGUF/resolve/main/Llama3-8B-Instruct-Replete-Adapted.i1-Q4_0.gguf) | i1-Q4_0 | 4.8 | fast, low quality |
+| [GGUF](https://huggingface.co/mradermacher/Llama3-8B-Instruct-Replete-Adapted-i1-GGUF/resolve/main/Llama3-8B-Instruct-Replete-Adapted.i1-Q4_K_S.gguf) | i1-Q4_K_S | 4.8 | optimal size/speed/quality |
+| [GGUF](https://huggingface.co/mradermacher/Llama3-8B-Instruct-Replete-Adapted-i1-GGUF/resolve/main/Llama3-8B-Instruct-Replete-Adapted.i1-Q4_K_M.gguf) | i1-Q4_K_M | 5.0 | fast, recommended |
+| [GGUF](https://huggingface.co/mradermacher/Llama3-8B-Instruct-Replete-Adapted-i1-GGUF/resolve/main/Llama3-8B-Instruct-Replete-Adapted.i1-Q5_K_S.gguf) | i1-Q5_K_S | 5.7 |  |
+| [GGUF](https://huggingface.co/mradermacher/Llama3-8B-Instruct-Replete-Adapted-i1-GGUF/resolve/main/Llama3-8B-Instruct-Replete-Adapted.i1-Q5_K_M.gguf) | i1-Q5_K_M | 5.8 |  |
+| [GGUF](https://huggingface.co/mradermacher/Llama3-8B-Instruct-Replete-Adapted-i1-GGUF/resolve/main/Llama3-8B-Instruct-Replete-Adapted.i1-Q6_K.gguf) | i1-Q6_K | 6.7 | practically like static Q6_K |
+
+Here is a handy graph by ikawrakow comparing some lower-quality quant
+types (lower is better):
+
+![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.png)
+
+And here are Artefact2's thoughts on the matter:
+https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9
+
+## FAQ / Model Request
+
+See https://huggingface.co/mradermacher/model_requests for some answers to
+questions you might have and/or if you want some other model quantized.
+
+## Thanks
+
+I thank my company, [nethype GmbH](https://www.nethype.de/), for letting
+me use its servers and providing upgrades to my workstation to enable
+this work in my free time. Additional thanks to [@nicoboss](https://huggingface.co/nicoboss) for giving me access to his hardware for calculating the imatrix for these quants.
+
+<!-- end -->