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Quant-Cartel/
Llama-3-TenyxChat-DaybreakStorywriter-70B-exl2-longcal

Name: Llama-3-TenyxChat-DaybreakStorywriter-70B-exl2-longcal
Availability: InStock

not-for-all-audiences

cc-by-nc-4.0

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Llama-3-TenyxChat-DaybreakStorywriter-70B-exl2-longcal

Quantized using 115 rows of 8192 tokens from the default ExLlamav2-calibration dataset.

Branches:

main -- measurement.json
6b8h -- 6bpw, 8bit lm_head
4.65b6h -- 4.65bpw, 6bit lm_head
2.25b6h -- 2.25bpw, 6bit lm_head

Original model link: Envoid/Llama-3-TenyxChat-DaybreakStorywriter-70B

Quanter's notes

As apparently the default dataset is supposed to be better in nearly all situations, I decided to start quanting using that in addition to my standard rpcal-fare. I'd appreciate real-world tests to confirm the hypothesis, though, so please leave a comment if you find this mode of quanting better than rpcal.

Original model README below.

Caution: This model is capable of producing adult content.

This model is a 50/50 SLERP merge between crestf411/L3-70B-daybreak-storywriter-v0.4

and

tenyx/Llama3-TenyxChat-70B

The resulting model scores significantly higher on the super top secret, private NALA evaluation (Neural-linguistic Assessment of Lifelike Approximation)^[1] making it a great choice for novelty RP scenarios.

TenyxChat-DaybreakStorywriter: 76.52

DeepSeek-Coder-V2-Instruct: 68.20

TenyxChat: 57.89

This model utilizes the Llama-3-Instruct prompt format.

^{1. The NALA evaluation is not a proper scientific evaluation and should not be used to inform any decisions related to personal safety, personal enjoyment, or any other critical or non-critical matter. NALA score is entirely arbitrary and subject to change without notice.}

Quant-Cartel/Llama-3-TenyxChat-DaybreakStorywriter-70B-exl2-longcal

Llama-3-TenyxChat-DaybreakStorywriter-70B-exl2-longcal

Quanter's notes

Caution: This model is capable of producing adult content.

Quant-Cartel/
Llama-3-TenyxChat-DaybreakStorywriter-70B-exl2-longcal