vanilj / gemma-2-ataraxy-9b

Made from Gemma 2 9B SPPO iter3 and SimPO

9B

84 Pulls Updated 2 weeks ago

2 weeks ago

de91a795fea7 · 4.8GB

model
gemma2
·
9.24B
·
Q3_K_M
params
{"stop":["<start_of_turn>","<end_of_turn>"]}
license
Gemma Terms of Use Last modified: April 1, 2024 By using, reproducing, modifying, distributing, performing or displaying any portion or element of Gemma, Model Derivatives including via any Hosted Service, (each as defined below) (collectively, the "Gemma Services") or otherwise accepting the terms of this Agreement, you agree to be bound by this Agreement. Section 1: DEFINITIONS 1.1 Definitions (a) "Agreement" or "Gemma Terms of Use" means these terms and conditions that govern the use, reproduction, Distribution or modification of the Gemma Services and any terms and conditions incorporated by reference. (b) "Distribution" or "Distribute" means any transmission, publication, or other sharing of Gemma or Model Derivatives to a third party, including by providing or making Gemma or its functionality available as a hosted service via API, web access, or any other electronic or remote means ("Hosted Service"). (c) "Gemma" means the set of machine learning language models, trained model weights and parameters identified at ai.google.dev/gemma, regardless of the source that you obtained it from. (d) "Google" means Google LLC. (e) "Model Derivatives" means all (i) modifications to Gemma, (ii) works based on Gemma, or (iii) any other machine learning model which is created by transfer of patterns of the weights, parameters, operations, or Output of Gemma, to that model in order to cause that model to perform similarly to Gemma, including distillation methods that use intermediate data representations or methods based on the generation of synthetic data Outputs by Gemma for training that model. For clarity, Outputs are not deemed Model Derivatives. (f) "Output" means the information content output of Gemma or a Model Derivative that results from operating or otherwise using Gemma or the Model Derivative, including via a Hosted Service. 1.2 As used in this Agreement, "including" means "including without limitation". Section 2: ELIGIBILITY AND USAGE 2.1 Eligibility You represent and warrant that you have the legal capacity to enter into this Agreement (including being of sufficient age of consent). If you are accessing or using any of the Gemma Services for or on behalf of a legal entity, (a) you are entering into this Agreement on behalf of yourself and that legal entity, (b) you represent and warrant that you have the authority to act on behalf of and bind that entity to this Agreement and (c) references to "you" or "your" in the remainder of this Agreement refers to both you (as an individual) and that entity. 2.2 Use You may use, reproduce, modify, Distribute, perform or display any of the Gemma Services only in accordance with the terms of this Agreement, and must not violate (or encourage or permit anyone else to violate) any term of this Agreement. Section 3: DISTRIBUTION AND RESTRICTIONS 3.1 Distribution and Redistribution You may reproduce or Distribute copies of Gemma or Model Derivatives if you meet all of the following conditions: You must include the use restrictions referenced in Section 3.2 as an enforceable provision in any agreement (e.g., license agreement, terms of use, etc.) governing the use and/or distribution of Gemma or Model Derivatives and you must provide notice to subsequent users you Distribute to that Gemma or Model Derivatives are subject to the use restrictions in Section 3.2. You must provide all third party recipients of Gemma or Model Derivatives a copy of this Agreement. You must cause any modified files to carry prominent notices stating that you modified the files. All Distributions (other than through a Hosted Service) must be accompanied by a "Notice" text file that contains the following notice: "Gemma is provided under and subject to the Gemma Terms of Use found at ai.google.dev/gemma/terms". You may add your own intellectual property statement to your modifications and, except as set forth in this Section, may provide additional or different terms and conditions for use, reproduction, or Distribution of your modifications, or for any such Model Derivatives as a whole, provided your use, reproduction, modification, Distribution, performance, and display of Gemma otherwise complies with the terms and conditions of this Agreement. Any additional or different terms and conditions you impose must not conflict with the terms of this Agreement. 3.2 Use Restrictions You must not use any of the Gemma Services: for the restricted uses set forth in the Gemma Prohibited Use Policy at ai.google.dev/gemma/prohibited_use_policy ("Prohibited Use Policy"), which is hereby incorporated by reference into this Agreement; or in violation of applicable laws and regulations. To the maximum extent permitted by law, Google reserves the right to restrict (remotely or otherwise) usage of any of the Gemma Services that Google reasonably believes are in violation of this Agreement. 3.3 Generated Output Google claims no rights in Outputs you generate using Gemma. You and your users are solely responsible for Outputs and their subsequent uses. Section 4: ADDITIONAL PROVISIONS 4.1 Updates Google may update Gemma from time to time. 4.2 Trademarks Nothing in this Agreement grants you any rights to use Google's trademarks, trade names, logos or to otherwise suggest endorsement or misrepresent the relationship between you and Google. Google reserves any rights not expressly granted herein. 4.3 DISCLAIMER OF WARRANTY UNLESS REQUIRED BY APPLICABLE LAW, THE GEMMA SERVICES, AND OUTPUTS, ARE PROVIDED ON AN "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, EITHER EXPRESS OR IMPLIED, INCLUDING ANY WARRANTIES OR CONDITIONS OF TITLE, NON-INFRINGEMENT, MERCHANTABILITY, OR FITNESS FOR A PARTICULAR PURPOSE. YOU ARE SOLELY RESPONSIBLE FOR DETERMINING THE APPROPRIATENESS OF USING, REPRODUCING, MODIFYING, PERFORMING, DISPLAYING OR DISTRIBUTING ANY OF THE GEMMA SERVICES OR OUTPUTS AND ASSUME ANY AND ALL RISKS ASSOCIATED WITH YOUR USE OR DISTRIBUTION OF ANY OF THE GEMMA SERVICES OR OUTPUTS AND YOUR EXERCISE OF RIGHTS AND PERMISSIONS UNDER THIS AGREEMENT. 4.4 LIMITATION OF LIABILITY TO THE FULLEST EXTENT PERMITTED BY APPLICABLE LAW, IN NO EVENT AND UNDER NO LEGAL THEORY, WHETHER IN TORT (INCLUDING NEGLIGENCE), PRODUCT LIABILITY, CONTRACT, OR OTHERWISE, UNLESS REQUIRED BY APPLICABLE LAW, SHALL GOOGLE OR ITS AFFILIATES BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY DIRECT, INDIRECT, SPECIAL, INCIDENTAL, EXEMPLARY, CONSEQUENTIAL, OR PUNITIVE DAMAGES, OR LOST PROFITS OF ANY KIND ARISING FROM THIS AGREEMENT OR RELATED TO, ANY OF THE GEMMA SERVICES OR OUTPUTS EVEN IF GOOGLE OR ITS AFFILIATES HAVE BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGES. 4.5 Term, Termination, and Survival The term of this Agreement will commence upon your acceptance of this Agreement (including acceptance by your use, modification, or Distribution, reproduction, performance or display of any portion or element of the Gemma Services) and will continue in full force and effect until terminated in accordance with the terms of this Agreement. Google may terminate this Agreement if you are in breach of any term of this Agreement. Upon termination of this Agreement, you must delete and cease use and Distribution of all copies of Gemma and Model Derivatives in your possession or control. Sections 1, 2.1, 3.3, 4.2 to 4.9 shall survive the termination of this Agreement. 4.6 Governing Law and Jurisdiction This Agreement will be governed by the laws of the State of California without regard to choice of law principles. The UN Convention on Contracts for the International Sale of Goods does not apply to this Agreement. The state and federal courts of Santa Clara County, California shall have exclusive jurisdiction of any dispute arising out of this Agreement. 4.7 Severability If any provision of this Agreement is held to be invalid, illegal or unenforceable, the remaining provisions shall be unaffected thereby and remain valid as if such provision had not been set forth herein. 4.8 Entire Agreement This Agreement states all the terms agreed between the parties and supersedes all other agreements between the parties as of the date of acceptance relating to its subject matter. 4.9 No Waiver Google will not be treated as having waived any rights by not exercising (or delaying the exercise of) any rights under this Agreement.
template
start_of_turn>user {{ if .System }}{{ .System }} {{ end }}{{ .Prompt }}<end_of_turn> <start_of_turn>model {{ .Response }}<end_of_turn>

Readme

GGUF files from bartowski/Gemma-2-Ataraxy-9B-GGUF

Gemma-2-Ataraxy-9B

Ataraxy

GGUF / EXL2 Quants

Huge thanks to @mradermacher and @bartowski for making these GGUF quants available to us.

Bartowski quants (imatrix): bartowski/Gemma-2-Ataraxy-9B-GGUF

Mradermacher quants (static): mradermacher/Gemma-2-Ataraxy-9B-GGUF

Mradermacher quants (imatrix): mradermacher/Gemma-2-Ataraxy-9B-i1-GGUF

I think bartowski and mradermacher use different calibration data for imatrix quants, or maybe you prefer static quants. Pick your poison :).

EXL2 quants from CameronRedmore: CameronRedmore/Gemma-2-Ataraxy-9B-exl2

Format

Use Gemma 2 format.

Benchmarks and Leaderboard Rankings

OpenLLM: Pending in Queue

Creative Writing V2 - Score: 82.64 (Rank 1)

https://eqbench.com/creative_writing.html

That’s right, much to everyone’s surprise (mine included) this model has topped eqbench.com’s creative writing benchmark. Big thanks to _sqrkl for taking the time to bother benchmarking this model and adding it ot his leaderboard, and @nbeerbower for entertaining my suggestions for his amazing gutenberg tunes.

Reddit

Leaderboard

Preface and Rambling

My favorite Gemma 2 9B models are the SPPO iter3 and SimPO finetunes, but I felt the slerp merge between the two (nephilim v3) wasn’t as good for some reason. The Gutenberg Gemma 2 finetune by nbeerbower is another my favorites. It’s trained on one of my favorite datasets, and actually improves the SPPO model’s average openllm leaderboard 2 average score by a bit, on top of improving it’s writing capabilities and making the LLM sound less AI-like. However I still liked the original SPPO finetune just a bit more.

Someone suggested that merging the base model on top of the gutenberg may help with tame it back down, which gave me a (possibly) better idea; slerp merging the SimPO finetune on top of the Gutenberg finetune, which is similar to the pretty popular Nephilim v3 recipe, using the Gutenberg finetune in place of the SPPO model, which I thought may give us better results since Gutenberg was trained on top of SPPO.

I wasn’t entirely too sure, since if nephilim v3 is anything to go by, it was probably going to also end up worse than the parent models. Normally when I try merges like these, they dont go anywhere. I’m pretty picky, and very skeptical usually, so most times I find that the merge is usually just not better than the original models or only marginally better. Tried this merge anyways to see how it goes, and much to my surprise, this time, I feel like I got very good results. Figured I’d share, and hopefully this wont be just me introducing more useless slop into a world that already has way too many unnecessary merges.

If you’re looking for a mistral nemo 12B model instead, I HIGHLY recommend Mistral Nemo Gutenberg v2 by nbeerbower. It’s head and shoulders above the many other mistral nemo finetunes I’ve tried (the first version of mistral nemo gutenburg, romulus simpo, and magnum mini 1.1 being close second favorites).

Why Gutenberg?

We use gutenberg 9b, which is finetuned over SPPO cause of how good the gutenberg dpo dataset is. It’s not a german dataset like it sounds, it’s a dataset based off of project gutenberg, a public domain collection of popular classic fictions, like Moby Dick, for example. This data set also uses LLM generated responses as the negative prompt, to train models to not sounds so much like AI, or your typical LLMs, and more like actual humans (based on the creative works from project gutenberg). This is quality writing, hence quality data, not just random RP logs, or synthetic data. This dataset, when trained for 3 epochs has shown to increase llama 3 average scores on the old openllm leaderboard, from 72 to 73 (nobody really got higher than 73 before the board revamp), and has already again, proven to increase average openllm 2 leaderboard scores, increasing the average score from 21.47 to 22.61, improving on sppo. Thats a huge improvement. That said, I didnt like gutenberg 9b more than original sppo in real use, felt a tiny bit overfit, so we tried this merge. Did not expect much, because of neph v3 turning out worse than either of its parents, but this surprisingly came out great.

Why is it 10b??

See https://github.com/arcee-ai/mergekit/issues/390

Model is not actually 10b, mergekit is randomly adding lm_head for some reason when doing SLERP merge with Gemma 2 models. I believe Nephilim v3 had a similar issue before they used some sort of workaround that I’m not aware of. Doesn’t seem like this affects the GGUF quants, as they’re the correct size, so I will leave it as is until mergekit gets a commit that addresses this issue.

Merge Details

Merge Method

This model was merged using the SLERP merge method.

Models Merged

The following models were included in the merge:
* princeton-nlp/gemma-2-9b-it-SimPO
* nbeerbower/gemma2-gutenberg-9B

Configuration

The following YAML configuration was used to produce this model:

base_model: nbeerbower/gemma2-gutenberg-9B
dtype: bfloat16
merge_method: slerp
parameters:
  t:
  - filter: self_attn
    value: [0.0, 0.5, 0.3, 0.7, 1.0]
  - filter: mlp
    value: [1.0, 0.5, 0.7, 0.3, 0.0]
  - value: 0.5
slices:
- sources:
  - layer_range: [0, 42]
    model: princeton-nlp/gemma-2-9b-it-SimPO
  - layer_range: [0, 42]
    model: nbeerbower/gemma2-gutenberg-9B