auto-patch README.md

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:  -->
 static quants of https://huggingface.co/Replete-AI/Llama3-8B-Instruct-Replete-Adapted
+
+<!-- provided-files -->
+weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.
+## 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-GGUF/resolve/main/Llama3-8B-Instruct-Replete-Adapted.Q2_K.gguf) | Q2_K | 3.3 |  |
+| [GGUF](https://huggingface.co/mradermacher/Llama3-8B-Instruct-Replete-Adapted-GGUF/resolve/main/Llama3-8B-Instruct-Replete-Adapted.IQ3_XS.gguf) | IQ3_XS | 3.6 |  |
+| [GGUF](https://huggingface.co/mradermacher/Llama3-8B-Instruct-Replete-Adapted-GGUF/resolve/main/Llama3-8B-Instruct-Replete-Adapted.Q3_K_S.gguf) | Q3_K_S | 3.8 |  |
+| [GGUF](https://huggingface.co/mradermacher/Llama3-8B-Instruct-Replete-Adapted-GGUF/resolve/main/Llama3-8B-Instruct-Replete-Adapted.IQ3_S.gguf) | IQ3_S | 3.8 | beats Q3_K* |
+| [GGUF](https://huggingface.co/mradermacher/Llama3-8B-Instruct-Replete-Adapted-GGUF/resolve/main/Llama3-8B-Instruct-Replete-Adapted.IQ3_M.gguf) | IQ3_M | 3.9 |  |
+| [GGUF](https://huggingface.co/mradermacher/Llama3-8B-Instruct-Replete-Adapted-GGUF/resolve/main/Llama3-8B-Instruct-Replete-Adapted.Q3_K_M.gguf) | Q3_K_M | 4.1 | lower quality |
+| [GGUF](https://huggingface.co/mradermacher/Llama3-8B-Instruct-Replete-Adapted-GGUF/resolve/main/Llama3-8B-Instruct-Replete-Adapted.Q3_K_L.gguf) | Q3_K_L | 4.4 |  |
+| [GGUF](https://huggingface.co/mradermacher/Llama3-8B-Instruct-Replete-Adapted-GGUF/resolve/main/Llama3-8B-Instruct-Replete-Adapted.IQ4_XS.gguf) | IQ4_XS | 4.6 |  |
+| [GGUF](https://huggingface.co/mradermacher/Llama3-8B-Instruct-Replete-Adapted-GGUF/resolve/main/Llama3-8B-Instruct-Replete-Adapted.Q4_K_S.gguf) | Q4_K_S | 4.8 | fast, recommended |
+| [GGUF](https://huggingface.co/mradermacher/Llama3-8B-Instruct-Replete-Adapted-GGUF/resolve/main/Llama3-8B-Instruct-Replete-Adapted.Q4_K_M.gguf) | Q4_K_M | 5.0 | fast, recommended |
+| [GGUF](https://huggingface.co/mradermacher/Llama3-8B-Instruct-Replete-Adapted-GGUF/resolve/main/Llama3-8B-Instruct-Replete-Adapted.Q5_K_S.gguf) | Q5_K_S | 5.7 |  |
+| [GGUF](https://huggingface.co/mradermacher/Llama3-8B-Instruct-Replete-Adapted-GGUF/resolve/main/Llama3-8B-Instruct-Replete-Adapted.Q5_K_M.gguf) | Q5_K_M | 5.8 |  |
+| [GGUF](https://huggingface.co/mradermacher/Llama3-8B-Instruct-Replete-Adapted-GGUF/resolve/main/Llama3-8B-Instruct-Replete-Adapted.Q6_K.gguf) | Q6_K | 6.7 | very good quality |
+| [GGUF](https://huggingface.co/mradermacher/Llama3-8B-Instruct-Replete-Adapted-GGUF/resolve/main/Llama3-8B-Instruct-Replete-Adapted.Q8_0.gguf) | Q8_0 | 8.6 | fast, best quality |
+| [GGUF](https://huggingface.co/mradermacher/Llama3-8B-Instruct-Replete-Adapted-GGUF/resolve/main/Llama3-8B-Instruct-Replete-Adapted.f16.gguf) | f16 | 16.2 | 16 bpw, overkill |
+
+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.
+
+<!-- end -->