auto-patch README.md

README.md

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+---
+base_model: 01-ai/yi-34b-200k
+datasets:
+- ai2_arc
+- allenai/ultrafeedback_binarized_cleaned
+- argilla/distilabel-intel-orca-dpo-pairs
+- jondurbin/airoboros-3.2
+- codeparrot/apps
+- facebook/belebele
+- bluemoon-fandom-1-1-rp-cleaned
+- boolq
+- camel-ai/biology
+- camel-ai/chemistry
+- camel-ai/math
+- camel-ai/physics
+- jondurbin/contextual-dpo-v0.1
+- jondurbin/gutenberg-dpo-v0.1
+- jondurbin/py-dpo-v0.1
+- jondurbin/truthy-dpo-v0.1
+- LDJnr/Capybara
+- jondurbin/cinematika-v0.1
+- WizardLM/WizardLM_evol_instruct_70k
+- glaiveai/glaive-function-calling-v2
+- jondurbin/gutenberg-dpo-v0.1
+- grimulkan/LimaRP-augmented
+- lmsys/lmsys-chat-1m
+- ParisNeo/lollms_aware_dataset
+- TIGER-Lab/MathInstruct
+- Muennighoff/natural-instructions
+- openbookqa
+- kingbri/PIPPA-shareGPT
+- piqa
+- Vezora/Tested-22k-Python-Alpaca
+- ropes
+- cakiki/rosetta-code
+- Open-Orca/SlimOrca
+- b-mc2/sql-create-context
+- squad_v2
+- mattpscott/airoboros-summarization
+- migtissera/Synthia-v1.3
+- unalignment/toxic-dpo-v0.2
+- WhiteRabbitNeo/WRN-Chapter-1
+- WhiteRabbitNeo/WRN-Chapter-2
+- winogrande
+exported_from: jondurbin/bagel-34b-v0.5
+language:
+- en
+library_name: transformers
+license: other
+license_link: https://huggingface.co/01-ai/Yi-34B-200K/blob/main/LICENSE
+license_name: yi-license
+quantized_by: mradermacher
+---
+## About
+
 <!-- ### convert_type:  -->
 <!-- ### vocab_type:  -->
 weighted/imatrix quants of https://huggingface.co/jondurbin/bagel-34b-v0.5
+
+
+<!-- provided-files -->
+static quants are available at https://huggingface.co/mradermacher/bagel-34b-v0.5-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-34b-v0.5-i1-GGUF/resolve/main/bagel-34b-v0.5.i1-Q2_K.gguf) | i1-Q2_K | 13.5 | IQ3_XXS probably better |
+| [GGUF](https://huggingface.co/mradermacher/bagel-34b-v0.5-i1-GGUF/resolve/main/bagel-34b-v0.5.i1-Q3_K_M.gguf) | i1-Q3_K_M | 17.3 | IQ3_S probably better |
+| [GGUF](https://huggingface.co/mradermacher/bagel-34b-v0.5-i1-GGUF/resolve/main/bagel-34b-v0.5.i1-Q4_K_S.gguf) | i1-Q4_K_S | 20.2 | optimal size/speed/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
+
+## 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 -->