LeroyDyer's picture
Update README.md
e447d38 verified
|
raw
history blame
No virus
2.35 kB
metadata
language:
  - en
license: mit
library_name: transformers
tags:
  - mergekit
  - merge
  - unsloth
base_model:
  - LeroyDyer/Mixtral_AI_CyberBrain_2.0
  - ezelikman/quietstar-8-ahead

hopefully this merge took correctly ! ....

Enabling for Thoughts to be displayed ;
here i have addded the extra tokens to the tokenizer ;

obviously untrained and will still need fine tuning ! as well as it has not been correctly coded for true management via transformers pretrained args. i will try to add the other arch: leaving it available to perhaps load with different remote auto mapping! , I will leve both automapping here and test both models to see which configuration loads correctly for training ! then wich loads correctly for usage ; as this also has been a minor issue ; the internall heads have default settings ; with remote code installed then its should be configuarble.

merge

This is a merge of pre-trained language models created using mergekit.

Merge Details

Merge Method

This model was merged using the SLERP merge method.

Models Merged

The following models were included in the merge:

Configuration

The following YAML configuration was used to produce this model:


slices:
  - sources:
      - model: LeroyDyer/Mixtral_AI_CyberBrain_2.0
        layer_range: [0, 32]
      - model: ezelikman/quietstar-8-ahead
        layer_range: [0, 32]
# or, the equivalent models: syntax:
# models:
#   - model: mistralai/Mistral-7B-Instruct-v0.2
# LaRGER MODEL MUST BE BASE  or
#  BASE MODEL MUST BE THE TOKENIZER YOU WISH TO ADOPT 
# so for models with customized processes they must be the base model
# If the base model has remote code then this must be collected and added 
# to the repo after and the config file adusted to allow for automapping to your new repo
#   - model: yanismiraoui/Yarn-Mistral-7b-128k-sharded
merge_method: slerp
base_model: ezelikman/quietstar-8-ahead
parameters:
  t:
    - filter: self_attn
      value: [0.3, 0.6, 0.3786, 0.6, 0.6]
    - filter: mlp
      value: [0.7, 0.4, 0.6, 0.4, 0.7]
    - value: 0.5 # fallback for rest of tensors
dtype: float16