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---
base_model:
- TheBloke/Llama-2-13B-fp16
- Masterjp123/SnowyRP-FinalV1-L2-13B
- Masterjp123/Snowyrp-V2B-P1
- sauce1337/BerrySauce-L2-13b
library_name: transformers
tags:
- mergekit
- merge
---
# Model
This is the Bf16 unquantized version of SnowyRP V2 Beta And the First Public Beta Model in the SnowyRP series of models!
[BF16](https://huggingface.co/Masterjp123/SnowyRP-V2-13B-L2_BetaTest)
[GGUF](https://huggingface.co/Masterjp123/SnowyRP-FinalV1-L2-13B-GGUF)
Any Future Quantizations I am made aware of will be added. sadly Gptq for Llama gave me errors so there will not be a GPTQ quantized model.
## Merge Details
just originally made V2beta to be a test, But it seems like it is good, So I am quantizing it.
These models CAN and WILL produce X rated or harmful content, due to being heavily uncensored in a attempt to not limit or make the model worse.
This Model has a Very good knowledge base and understands anatomy decently, Plus this Model is VERY versitle and is great for General assistant work, RP and ERP, RPG RPs and much more.
## Model Use:
This model is very good... WITH THE RIGHT SETTINGS.
I personally use microstat mixed with dynamic temp with epsion cut off and eta cut off.
```
Optimal Settings (so far)
Microstat Mode: 2
tau: 2.95
eta: 0.05
Dynamic Temp
min: 0.25
max: 1.8
Cut offs
epsilon: 3
eta: 3
```
### Merge Method
This model was merged using the [ties](https://arxiv.org/abs/2306.01708) merge method using [TheBloke/Llama-2-13B-fp16](https://huggingface.co/TheBloke/Llama-2-13B-fp16) as a base.
### Models Merged
The following models were included in the merge:
* [Masterjp123/SnowyRP-FinalV1-L2-13B](https://huggingface.co/Masterjp123/SnowyRP-FinalV1-L2-13B)
* [posicube/Llama2-chat-AYB-13B](https://huggingface.co/posicube/Llama2-chat-AYB-13B)
* [Sao10K/Stheno-1.8-L2-13B](https://huggingface.co/Sao10K/Stheno-1.8-L2-13B)
* [ValiantLabs/ShiningValiantXS](https://huggingface.co/ValiantLabs/ShiningValiantXS)
* [sauce1337/BerrySauce-L2-13b](https://huggingface.co/sauce1337/BerrySauce-L2-13b)
### Configuration
The following YAML configuration was used to produce this model:
```yaml
base_model:
model:
path: TheBloke/Llama-2-13B-fp16
dtype: bfloat16
merge_method: ties
parameters:
int8_mask: 1.0
normalize: 1.0
slices:
- sources:
- layer_range: [0, 40]
model:
model:
path: Masterjp123/Snowyrp-V2B-P1
parameters:
density: [1.0, 0.7, 0.1]
weight: 1.0
- layer_range: [0, 40]
model:
model:
path: Masterjp123/SnowyRP-FinalV1-L2-13B
parameters:
density: 0.5
weight: [0.0, 0.3, 0.7, 1.0]
- layer_range: [0, 40]
model:
model:
path: sauce1337/BerrySauce-L2-13b
parameters:
density: 0.33
weight:
- filter: mlp
value: 0.5
- value: 0.0
- layer_range: [0, 40]
model:
model:
path: TheBloke/Llama-2-13B-fp16
```
for Masterjp123/Snowyrp-V2B-P1
```yaml
base_model:
model:
path: TheBloke/Llama-2-13B-fp16
dtype: bfloat16
merge_method: ties
parameters:
int8_mask: 1.0
normalize: 1.0
slices:
- sources:
- layer_range: [0, 40]
model:
model:
path: Sao10K/Stheno-1.8-L2-13B
parameters:
density: [1.0, 0.7, 0.1]
weight: 1.0
- layer_range: [0, 40]
model:
model:
path: ValiantLabs/ShiningValiantXS
parameters:
density: 0.5
weight: [0.0, 0.3, 0.7, 1.0]
- layer_range: [0, 40]
model:
model:
path: posicube/Llama2-chat-AYB-13B
parameters:
density: 0.33
weight:
- filter: mlp
value: 0.5
- value: 0.0
- layer_range: [0, 40]
model:
model:
path: TheBloke/Llama-2-13B-fp16
```
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