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metadata
base_model: jondurbin/bagel-8b-v1.0
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
language:
  - en
library_name: transformers
license: other
license_link: https://huggingface.co/meta-llama/Meta-Llama-3-8B/blob/main/LICENSE
license_name: llama3
quantized_by: mradermacher
tags:
  - llama-3
  - bagel

About

static quants of https://huggingface.co/jondurbin/bagel-8b-v1.0

weighted/imatrix quants are available at https://huggingface.co/mradermacher/bagel-8b-v1.0-i1-GGUF

Usage

If you are unsure how to use GGUF files, refer to one of TheBloke's READMEs 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 Q2_K 3.3
GGUF IQ3_XS 3.6
GGUF Q3_K_S 3.8
GGUF IQ3_S 3.8 beats Q3_K*
GGUF IQ3_M 3.9
GGUF Q3_K_M 4.1 lower quality
GGUF Q3_K_L 4.4
GGUF IQ4_XS 4.6
GGUF Q4_K_S 4.8 fast, recommended
GGUF Q4_K_M 5.0 fast, recommended
GGUF Q5_K_S 5.7
GGUF Q5_K_M 5.8
GGUF Q6_K 6.7 very good quality
GGUF Q8_0 8.6 fast, best quality
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

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, for letting me use its servers and providing upgrades to my workstation to enable this work in my free time.