metadata
license: cc-by-nc-4.0
Description
This repo contains bf16 files of Nyxene-v1-11B. Just new version with some new things.
Model used
- Intel/neural-chat-7b-v3-3-Slerp
- AIDC-ai-business/Marcoroni-7B-v3
- rwitz/go-bruins-v2
- chargoddard/loyal-piano-m7-cdpo
Prompt template
Just use chatml.
The secret sauce
go-bruins-loyal-piano-11B :
slices:
- sources:
- model: rwitz/go-bruins-v2
layer_range: [0, 24]
- sources:
- model: chargoddard/loyal-piano-m7-cdpo
layer_range: [8, 32]
merge_method: passthrough
dtype: bfloat16
neural-marcoroni-11B :
slices:
- sources:
- model: AIDC-ai-business/Marcoroni-7B-v3
layer_range: [0, 24]
- sources:
- model: Intel/neural-chat-7b-v3-3-Slerp
layer_range: [8, 32]
merge_method: passthrough
dtype: bfloat16
Nyxene-11B :
slices:
- sources:
- model: "./go-bruins-loyal-piano-11B"
layer_range: [0, 48]
- model: "./neural-marcoroni-11B"
layer_range: [0, 48]
merge_method: slerp
base_model: "./go-bruins-loyal-piano-11B"
parameters:
t:
- filter: lm_head
value: [0.5]
- filter: embed_tokens
value: [0.75]
- filter: self_attn
value: [0.75, 0.25]
- filter: mlp
value: [0.25, 0.75]
- filter: layernorm
value: [0.5, 0.5]
- filter: modelnorm
value: [0.5]
- value: 0.5 # fallback for rest of tensors
dtype: bfloat16
I use mergekit for all the manipulation told here.
Thanks to the Undi95 for the original 11B mistral merge recipe.