Inschrift Spruch Raum
Inschrift-Spruch-Raum
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replied to
sometimesanotion's
post
8 days ago
I'd like to draw your attention to a Lamarck-based experiment which uses Arcee AI's newly published arcee_fusion merge method for three out of its four merges. Yes, just four. This is a simple one, and its recipe is fully open:
https://huggingface.co/sometimesanotion/Lamarck-14B-v0.7-Fusion
It unifies three branches, all of which feature models which bring Lamarck-14B-v0.7 and Qwenvergence-14B-v12-Prose together. One side features @jpacifico's http://huggingface.co/jpacifico/Chocolatine-2-14B-Instruct-v2.0.3 and the other features @suayptalha's http://huggingface.co/suayptalha/Lamarckvergence-14B paired with my models which were their merge ancestors.
A fusion merge - of a fusion merge and a SLERP of a fusion and older merge - should demonstrate the new merge method's behavior in interesting ways, especially in the first 1/4th of the model where the SLERP has less impact.
I welcome you to kick the tires and learn from it. It has prose quality near Qwenvergence v12's - as you'd expect.
Thank you, @mradermacher and @MaziyarPanahi, for the first-day quantizations! Your work helped get me started. https://huggingface.co/models?other=base_model:quantized:sometimesanotion/Lamarck-14B-v0.7-Fusion
replied to
sometimesanotion's
post
9 days ago
I'd like to draw your attention to a Lamarck-based experiment which uses Arcee AI's newly published arcee_fusion merge method for three out of its four merges. Yes, just four. This is a simple one, and its recipe is fully open:
https://huggingface.co/sometimesanotion/Lamarck-14B-v0.7-Fusion
It unifies three branches, all of which feature models which bring Lamarck-14B-v0.7 and Qwenvergence-14B-v12-Prose together. One side features @jpacifico's http://huggingface.co/jpacifico/Chocolatine-2-14B-Instruct-v2.0.3 and the other features @suayptalha's http://huggingface.co/suayptalha/Lamarckvergence-14B paired with my models which were their merge ancestors.
A fusion merge - of a fusion merge and a SLERP of a fusion and older merge - should demonstrate the new merge method's behavior in interesting ways, especially in the first 1/4th of the model where the SLERP has less impact.
I welcome you to kick the tires and learn from it. It has prose quality near Qwenvergence v12's - as you'd expect.
Thank you, @mradermacher and @MaziyarPanahi, for the first-day quantizations! Your work helped get me started. https://huggingface.co/models?other=base_model:quantized:sometimesanotion/Lamarck-14B-v0.7-Fusion
replied to
sometimesanotion's
post
about 2 months ago
I'm just saving today's 14B parameter chart, because big things are about to hit. Lamarck v0.7 has been surpassed by at least two models I know of, and in ways that promise good things to come for the whole scene. I am taking my time to enjoy the progress, and Lamarck v0.8 will come when it's clearly keeping up and keeping its flavor.
There is no one best model for everyone, regardless of these rankings. I aim to make Lamarck good at coding, translating, and rigorously critiquing rhetoric and logic. Always check out the authors' notes on models to see if their intent is close to your use case!
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How are its various parameters
5
#1 opened about 2 months ago
by
Inschrift-Spruch-Raum
How are its various parameters
5
#1 opened about 2 months ago
by
Inschrift-Spruch-Raum