Best way to achieve 16k context withing 8GB of vram while achieving as much context as possible
The Mistral 0.2 version of Erosumika-7B-v3, a DARE TIES merge between Nitral's
Kunocchini-7b, Endevor's
InfinityRP-v1-7B and my
FlatErosAlpha, a flattened(in order to keep the vocab size 32000) version of tavtav's
eros-7B-ALPHA. Alpaca and ChatML work best. Slightly smarter and better prompt comprehension than Mistral 0.1 Erosumika-7B-v3. 32k context should work.
The intended use-case for this model is fictional writing for entertainment purposes. Any other sort of usage is out of scope.
It may produce socially unacceptable or undesirable text, even if the prompt itself does not include anything explicitly offensive. Outputs might often be factually wrong or misleading.
1merge_method: task_arithmetic
2base_model: alpindale/Mistral-7B-v0.2-hf
3models:
4 - model: localfultonextractor/Erosumika-7B-v3
5 parameters:
6 weight: 1.0
7dtype: float16
