transformers gguf llama-3 bagel en dataset:ai2_arc dataset:allenai/ultrafeedback_binarized_cleaned dataset:argilla/distilabel-intel-orca-dpo-pairs dataset:jondurbin/airoboros-3.2 dataset:codeparrot/apps dataset:facebook/belebele dataset:bluemoon-fandom-1-1-rp-cleaned dataset:boolq dataset:camel-ai/biology dataset:camel-ai/chemistry dataset:camel-ai/math dataset:camel-ai/physics dataset:jondurbin/contextual-dpo-v0.1 dataset:jondurbin/gutenberg-dpo-v0.1 dataset:jondurbin/py-dpo-v0.1 dataset:jondurbin/truthy-dpo-v0.1 dataset:LDJnr/Capybara dataset:jondurbin/cinematika-v0.1 dataset:WizardLM/WizardLM_evol_instruct_70k dataset:glaiveai/glaive-function-calling-v2 dataset:grimulkan/LimaRP-augmented dataset:lmsys/lmsys-chat-1m dataset:ParisNeo/lollms_aware_dataset dataset:TIGER-Lab/MathInstruct dataset:Muennighoff/natural-instructions dataset:openbookqa dataset:kingbri/PIPPA-shareGPT dataset:piqa dataset:Vezora/Tested-22k-Python-Alpaca dataset:ropes dataset:cakiki/rosetta-code dataset:Open-Orca/SlimOrca dataset:b-mc2/sql-create-context dataset:squad_v2 dataset:mattpscott/airoboros-summarization dataset:migtissera/Synthia-v1.3 dataset:unalignment/toxic-dpo-v0.2 dataset:WhiteRabbitNeo/WRN-Chapter-1 dataset:WhiteRabbitNeo/WRN-Chapter-2 dataset:winogrande base_model:jondurbin/bagel-8b-v1.0 base_model:quantized:jondurbin/bagel-8b-v1.0 license:other endpoints_compatible region:us conversational
---
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_name: llama3
license_link: https://huggingface.co/meta-llama/Meta-Llama-3-8B/blob/main/LICENSE
tags:
- llama-3
- bagel
quantized_by: mradermacher
---
## About

<!-- ### quantize_version: 1 -->
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weighted/imatrix quants of https://huggingface.co/jondurbin/bagel-8b-v1.0

<!-- provided-files -->
static quants are available at https://huggingface.co/mradermacher/bagel-8b-v1.0-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-8b-v1.0-i1-GGUF/resolve/main/bagel-8b-v1.0.i1-IQ1_S.gguf) | i1-IQ1_S | 2.1 | for the desperate |
| [GGUF](https://huggingface.co/mradermacher/bagel-8b-v1.0-i1-GGUF/resolve/main/bagel-8b-v1.0.i1-IQ1_M.gguf) | i1-IQ1_M | 2.3 | mostly desperate |
| [GGUF](https://huggingface.co/mradermacher/bagel-8b-v1.0-i1-GGUF/resolve/main/bagel-8b-v1.0.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 2.5 |  |
| [GGUF](https://huggingface.co/mradermacher/bagel-8b-v1.0-i1-GGUF/resolve/main/bagel-8b-v1.0.i1-IQ2_XS.gguf) | i1-IQ2_XS | 2.7 |  |
| [GGUF](https://huggingface.co/mradermacher/bagel-8b-v1.0-i1-GGUF/resolve/main/bagel-8b-v1.0.i1-IQ2_S.gguf) | i1-IQ2_S | 2.9 |  |
| [GGUF](https://huggingface.co/mradermacher/bagel-8b-v1.0-i1-GGUF/resolve/main/bagel-8b-v1.0.i1-IQ2_M.gguf) | i1-IQ2_M | 3.0 |  |
| [GGUF](https://huggingface.co/mradermacher/bagel-8b-v1.0-i1-GGUF/resolve/main/bagel-8b-v1.0.i1-Q2_K.gguf) | i1-Q2_K | 3.3 | IQ3_XXS probably better |
| [GGUF](https://huggingface.co/mradermacher/bagel-8b-v1.0-i1-GGUF/resolve/main/bagel-8b-v1.0.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 3.4 | lower quality |
| [GGUF](https://huggingface.co/mradermacher/bagel-8b-v1.0-i1-GGUF/resolve/main/bagel-8b-v1.0.i1-IQ3_XS.gguf) | i1-IQ3_XS | 3.6 |  |
| [GGUF](https://huggingface.co/mradermacher/bagel-8b-v1.0-i1-GGUF/resolve/main/bagel-8b-v1.0.i1-Q3_K_S.gguf) | i1-Q3_K_S | 3.8 | IQ3_XS probably better |
| [GGUF](https://huggingface.co/mradermacher/bagel-8b-v1.0-i1-GGUF/resolve/main/bagel-8b-v1.0.i1-IQ3_S.gguf) | i1-IQ3_S | 3.8 | beats Q3_K* |
| [GGUF](https://huggingface.co/mradermacher/bagel-8b-v1.0-i1-GGUF/resolve/main/bagel-8b-v1.0.i1-IQ3_M.gguf) | i1-IQ3_M | 3.9 |  |
| [GGUF](https://huggingface.co/mradermacher/bagel-8b-v1.0-i1-GGUF/resolve/main/bagel-8b-v1.0.i1-Q3_K_M.gguf) | i1-Q3_K_M | 4.1 | IQ3_S probably better |
| [GGUF](https://huggingface.co/mradermacher/bagel-8b-v1.0-i1-GGUF/resolve/main/bagel-8b-v1.0.i1-Q3_K_L.gguf) | i1-Q3_K_L | 4.4 | IQ3_M probably better |
| [GGUF](https://huggingface.co/mradermacher/bagel-8b-v1.0-i1-GGUF/resolve/main/bagel-8b-v1.0.i1-IQ4_XS.gguf) | i1-IQ4_XS | 4.5 |  |
| [GGUF](https://huggingface.co/mradermacher/bagel-8b-v1.0-i1-GGUF/resolve/main/bagel-8b-v1.0.i1-Q4_0.gguf) | i1-Q4_0 | 4.8 | fast, low quality |
| [GGUF](https://huggingface.co/mradermacher/bagel-8b-v1.0-i1-GGUF/resolve/main/bagel-8b-v1.0.i1-Q4_K_S.gguf) | i1-Q4_K_S | 4.8 | optimal size/speed/quality |
| [GGUF](https://huggingface.co/mradermacher/bagel-8b-v1.0-i1-GGUF/resolve/main/bagel-8b-v1.0.i1-Q4_K_M.gguf) | i1-Q4_K_M | 5.0 | fast, recommended |
| [GGUF](https://huggingface.co/mradermacher/bagel-8b-v1.0-i1-GGUF/resolve/main/bagel-8b-v1.0.i1-Q5_K_S.gguf) | i1-Q5_K_S | 5.7 |  |
| [GGUF](https://huggingface.co/mradermacher/bagel-8b-v1.0-i1-GGUF/resolve/main/bagel-8b-v1.0.i1-Q5_K_M.gguf) | i1-Q5_K_M | 5.8 |  |
| [GGUF](https://huggingface.co/mradermacher/bagel-8b-v1.0-i1-GGUF/resolve/main/bagel-8b-v1.0.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.

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