Downloads · 30 days
5
25% of all-time downloads
async0x42/Merged-RP-Stew-V2-34B-exl2_5bpw
Merged-RP-Stew-V2-34B-exl2_5bpw is a machine learning model from async0x42. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
This is a merge of pre-trained language models created using mergekit.
Downloads · 30 days
5
25% of all-time downloads
All-time downloads
20
Public
Repo size
22.2 GB
Likes
0
Public
Click a slice to open those files.
.safetensors22.2 GB · 100%
From the Hugging Face model README
This is a merge of pre-trained language models created using mergekit.
Specialized exl2 versions can be found here:
3.5 - https://huggingface.co/ParasiticRogue/Merged-RP-Stew-V2-34B-exl2-3.5?not-for-all-audiences=true
4.0 - https://huggingface.co/ParasiticRogue/Merged-RP-Stew-V2-34B-exl2-4.0?not-for-all-audiences=true
4.65 - https://huggingface.co/ParasiticRogue/Merged-RP-Stew-V2-34B-exl2-4.65-fix?not-for-all-audiences=true
5.0 - https://huggingface.co/ParasiticRogue/Merged-RP-Stew-V2-34B-exl2-5.0?not-for-all-audiences=true
6.0~8.0 provided by Dracones:
6.0 - https://huggingface.co/Dracones/Merged-RP-Stew-V2-34B_exl2_6.0bpw?not-for-all-audiences=true
7.0 - https://huggingface.co/Dracones/Merged-RP-Stew-V2-34B_exl2_7.0bpw?not-for-all-audiences=true
8.0 - https://huggingface.co/Dracones/Merged-RP-Stew-V2-34B_exl2_8.0bpw?not-for-all-audiences=true
Standardized GGUFs provided by MarsupialAI (Doesn't use Bluemoon-Light parquet):
https://huggingface.co/MarsupialAI/Merged-RP-Stew-V2-34B_iMatrix_GGUF?not-for-all-audiences=true
New pot of stew with some slight seasoning added into the merging recipe. Besides being decent models, Capybara was chosen at a higher percentage for it's general aptitude plus preserving longer context length, Tess-1.5 is for better character/lore understanding, Nontoxic-Bagel SLERPed with PiVoT-SUS-RP (seperate from the main merge) is for chat/RP and storytelling diversity, while Nyakura SLERPed into CausalLM-RP is for even better chat/RP engagement. Both Nontoxic-Bagel and CausalLM-RP were used as the base of their respective SLERPs.
Big thanks to the original model creators, while special thanks goes to brucethemoose, SanjiWatsuki, and MarinaraSpaghetti for general ideas and help as well!
Temperature @ 0.93
Min-P @ 0.02
Typical-P @ 0.9
Repetition Penalty @ 1.07
Repetition Range @ 2048
Smoothing Factor @ 0.39
Smoothing Curve @ 2
Everything else @ off
Early Stopping = X
Do Sample = ✓
Add BOS Token = X
Ban EOS Token = ✓
Skip Special Tokens = ✓
Temperature Last = ✓
Custom Stopping Strings: "< / s >" (<---without spaces)
However for those who want more control using the system prompt, well...let's just say the length is going to be biblical in nature.
You are {{char}}; an autonomous entity in this living open-ended chat with me, {{user}}. It is vital that you follow the 10 CHAT COMMANDMENTS instructed below in order for universal stability, since our life depends on it!
<10 CHAT COMMANDMENTS>
Fun little addition you can add to the end of the 2nd commandment if you want your characters to act more lifelike in sillytavern (or possibly elsewhere):
...being newly introduced alongside, making sure to give yourself a unique personal inner voice at the beginning of messages before conversing further using this example container: [](#' {{char}}'s subconscious feelings/opinion. ').
It doesn't work all the time, and you may need to force the AI to use it during the first few messages, but it will catch on after awhile. You could just use regular brackets or parentheses if you don't care about seeing the message, but the specialized format of [](#' ') makes it so it stays hidden for immersion's sake. it's important to put it at the beginning of their message, rather then at the end, so it can be used as a guide for them.
For settings that are more in depth try this:
SYSTEM:
{system_prompt}<|im_end|>
USER:
{prompt}<|im_end|>
ASSISTANT:
{output}<|im_end|>
Yes, this is just ChatML mixed with Vicuna, but without the im_start tokens, and the characters are capitalized. it's a compromise in keeping it both creative and under control, trying to pull from both sources. It works in testing, but you can use the vanilla versions of either if you really want to.
The following models were included in the merge:
https://huggingface.co/NousResearch/Nous-Capybara-34B
https://huggingface.co/migtissera/Tess-34B-v1.5b
https://huggingface.co/jondurbin/nontoxic-bagel-34b-v0.2
https://huggingface.co/maywell/PiVoT-SUS-RP
https://huggingface.co/Sao10K/NyakuraV2-34B-Yi-Llama
https://huggingface.co/NeverSleep/CausalLM-RP-34B
https://huggingface.co/chargoddard/Yi-34B-200K-Llama
The following YAML configuration was used to produce this model:
models:
- model: Nyakura-CausalLM-RP-34B
parameters:
weight: 0.16
density: 0.42
- model: Nontoxic-PiVoT-Bagel-RP-34b
parameters:
weight: 0.22
density: 0.54
- model: Tess-34B-v1.5b
parameters:
weight: 0.28
density: 0.66
- model: Nous-Capybara-34B-V1.9
parameters:
weight: 0.34
density: 0.78
merge_method: dare_ties
base_model: Yi-34B-200K-Llama
parameters:
int8_mask: true
dtype: bfloat16