Note
fifth try is the charm on this quant, it seems. been getting too many issues with runpod lately, it's a huge pain to have to rerun a bunch of crap because the pods lose internet and a bunch of other issues.
On with the show!
Quantized using 200 samples of 8192 tokens from an RP-oriented PIPPA dataset.
Branches:
main
--measurement.json
2.25b6h
-- 2.25bpw, 6bit lm_head3.5b6h
-- 3.5bpw, 6bit lm_head6b6h
-- 6bpw, 6bit lm_head
Requires ExllamaV2 version 0.0.12 and up.
Original model link: rAIfle/Sloppy-Wingman-8x7B-hf
Original model README below.
Sloppy-Wingman-8x7B-hf
Big slop, good model. Running better at slightly higher temp (1.1-ish) than usual, along with 0.05 MinP and 0.28 snoot. Bog-standard ChatML works best imo, but Alpaca and Mixtral formats work (to some degree) too.
Parts:
models:
- model: mistralai/Mixtral-8x7B-v0.1+retrieval-bar/Mixtral-8x7B-v0.1_case-briefs
parameters:
weight: 0.33
- model: mistralai/Mixtral-8x7B-v0.1+wandb/Mixtral-8x7b-Remixtral
parameters:
weight: 0.33
merge_method: task_arithmetic
base_model: mistralai/Mixtral-8x7B-v0.1
dtype: float16
and
models:
- model: mistralai/Mixtral-8x7B-Instruct-v0.1+/ai/LLM/tmp/pefts/daybreak-peft/mixtral-8x7b
parameters:
weight: 0.85
- model: notstoic/Nous-Hermes-2-Mixtruct-v0.1-8x7B-DPO-DARE_TIES
parameters:
weight: 0.25
- model: ycros/BagelWorldTour-8x7B
parameters:
weight: 0.1
merge_method: task_arithmetic
base_model: mistralai/Mixtral-8x7B-Instruct-v0.1
dtype: float16
SLERP:ed together as per below.
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:
- ./02-friend2-instruct
- ./01-friend2-base
Configuration
The following YAML configuration was used to produce this model:
models:
- model: ./01-friend2-base
- model: ./02-friend2-instruct
merge_method: slerp
base_model: ./01-friend2-base
parameters:
t:
- value: 0.5
dtype: float16