Not-For-All-Audiences
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---
license: cc-by-nc-4.0
tags:
- not-for-all-audiences
---
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PROUDLY PRESENTS
```
# Llama-3-TenyxChat-DaybreakStorywriter-70B-exl2-rpcal
Quantized using 200 samples of 8192 tokens from an RP-oriented [PIPPA](https://huggingface.co/datasets/royallab/PIPPA-cleaned) 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](https://huggingface.co/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 rpcal to be better than what I've dubbed 'longcal'.
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](https://huggingface.co/crestf411/L3-70B-daybreak-storywriter-v0.4)
and
[tenyx/Llama3-TenyxChat-70B](https://huggingface.co/tenyx/Llama3-TenyxChat-70B)
The resulting model scores significantly higher on the super top secret, private **NALA** evaluation *(Neural-linguistic Assessment of Lifelike Approximation)*<sup>[1]</sup> 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.
<sup>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.</sup>
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