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---
license: apache-2.0
datasets:
- Epiculous/SynthRP-Gens-v1.1-Filtered-n-Cleaned
- anthracite-org/stheno-filtered-v1.1
- PJMixers/hieunguyenminh_roleplay-deduped-ShareGPT
- Gryphe/Sonnet3.5-Charcard-Roleplay
- Epiculous/Synthstruct-Gens-v1.1-Filtered-n-Cleaned
- anthracite-org/kalo-opus-instruct-22k-no-refusal
- anthracite-org/nopm_claude_writing_fixed
- anthracite-org/kalo_opus_misc_240827
language:
- en
- fr
- de
- es
- it
- pt
- ru
- zh
- ja
pipeline_tag: text-generation
tags:
- merge
---
### exl2 quant (measurement.json in main branch)
---
### check revisions for quants
---
Now for something a bit different, Violet_Twilight-v0.2! This model is a SLERP merge of Azure_Dusk-v0.2 and Crimson_Dawn-v0.2!
# Quants!
<strong>full</strong> / [exl2]() / [gguf]()
## Prompting
The v0.2 models are trained on ChatML, the prompting structure goes a little something like this:
```
<|im_start|>user
Hi there!<|im_end|>
<|im_start|>assistant
Nice to meet you!<|im_end|>
<|im_start|>user
Can I ask a question?<|im_end|>
<|im_start|>assistant
```
### Context and Instruct
The v0.2 models are trained on ChatML, please use that Context and Instruct template.
### Current Top Sampler Settings
[Spicy_Temp](https://files.catbox.moe/9npj0z.json) <br/>
[Violet_Twilight-Nitral-Special](https://files.catbox.moe/ot54u3.json) <br/>
## Merging
The following config was used to merge Azure Dusk and Crimson Dawn
```yaml
slices:
- sources:
- model: Epiculous/Azure_Dusk-v0.2
layer_range: [0, 40]
- model: Epiculous/Crimson_Dawn-V0.2
layer_range: [0, 40]
merge_method: slerp
base_model: Epiculous/Azure_Dusk-v0.2
parameters:
t:
- filter: self_attn
value: [0, 0.5, 0.3, 0.7, 1]
- filter: mlp
value: [1, 0.5, 0.7, 0.3, 0]
- value: 0.5 # fallback for rest of tensors
dtype: bfloat16
``` |