auto-patch README.md

README.md

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+---
+base_model: jondurbin/bagel-8x7b-v0.2
+datasets:
+- ai2_arc
+- jondurbin/airoboros-3.2
+- codeparrot/apps
+- facebook/belebele
+- boolq
+- jondurbin/cinematika-v0.1
+- drop
+- lmsys/lmsys-chat-1m
+- TIGER-Lab/MathInstruct
+- cais/mmlu
+- Muennighoff/natural-instructions
+- openbookqa
+- piqa
+- Vezora/Tested-22k-Python-Alpaca
+- cakiki/rosetta-code
+- Open-Orca/SlimOrca
+- spider
+- squad_v2
+- migtissera/Synthia-v1.3
+- datasets/winogrande
+- nvidia/HelpSteer
+- Intel/orca_dpo_pairs
+- unalignment/toxic-dpo-v0.1
+- jondurbin/truthy-dpo-v0.1
+- allenai/ultrafeedback_binarized_cleaned
+- Squish42/bluemoon-fandom-1-1-rp-cleaned
+- LDJnr/Capybara
+- JULIELab/EmoBank
+- kingbri/PIPPA-shareGPT
+language:
+- en
+library_name: transformers
+license: apache-2.0
+quantized_by: mradermacher
+---
+## About
+
 <!-- ### quantize_version: 2 -->
 <!-- ### output_tensor_quantised: 1 -->
 <!-- ### convert_type: hf -->
 <!-- ### vocab_type:  -->
 <!-- ### tags: nicoboss -->
 static quants of https://huggingface.co/jondurbin/bagel-8x7b-v0.2
+
+<!-- provided-files -->
+weighted/imatrix quants are available at https://huggingface.co/mradermacher/bagel-8x7b-v0.2-i1-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/bagel-8x7b-v0.2-GGUF/resolve/main/bagel-8x7b-v0.2.Q2_K.gguf) | Q2_K | 17.4 |  |
+| [GGUF](https://huggingface.co/mradermacher/bagel-8x7b-v0.2-GGUF/resolve/main/bagel-8x7b-v0.2.Q3_K_S.gguf) | Q3_K_S | 20.5 |  |
+| [GGUF](https://huggingface.co/mradermacher/bagel-8x7b-v0.2-GGUF/resolve/main/bagel-8x7b-v0.2.Q3_K_M.gguf) | Q3_K_M | 22.6 | lower quality |
+| [GGUF](https://huggingface.co/mradermacher/bagel-8x7b-v0.2-GGUF/resolve/main/bagel-8x7b-v0.2.Q3_K_L.gguf) | Q3_K_L | 24.3 |  |
+| [GGUF](https://huggingface.co/mradermacher/bagel-8x7b-v0.2-GGUF/resolve/main/bagel-8x7b-v0.2.Q4_K_S.gguf) | Q4_K_S | 26.8 | fast, recommended |
+| [GGUF](https://huggingface.co/mradermacher/bagel-8x7b-v0.2-GGUF/resolve/main/bagel-8x7b-v0.2.Q4_K_M.gguf) | Q4_K_M | 28.5 | fast, recommended |
+| [GGUF](https://huggingface.co/mradermacher/bagel-8x7b-v0.2-GGUF/resolve/main/bagel-8x7b-v0.2.Q5_K_S.gguf) | Q5_K_S | 32.3 |  |
+| [GGUF](https://huggingface.co/mradermacher/bagel-8x7b-v0.2-GGUF/resolve/main/bagel-8x7b-v0.2.Q6_K.gguf) | Q6_K | 38.5 | very good quality |
+| [GGUF](https://huggingface.co/mradermacher/bagel-8x7b-v0.2-GGUF/resolve/main/bagel-8x7b-v0.2.Q8_0.gguf) | Q8_0 | 49.7 | fast, best quality |
+
+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 private supercomputer, enabling me to provide many more imatrix quants, at much higher quality, than I would otherwise be able to.
+
+<!-- end -->