YAML Metadata Warning: The pipeline tag "text2text-generation" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, audio-text-to-text, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-ranking, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, image-text-to-image, image-text-to-video, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, video-text-to-text, keypoint-detection, visual-document-retrieval, any-to-any, video-to-video, other
If anybody has star trek data please send as this starship computer database archive needs it!
then i can correctly theme this model to be inside its role as a starship computer : so as well as any space dara ffrom nasa ; i have collected some mufon files which i am still framing the correct prompts for ; for recall as well as interogation : I shall also be adding a lot of biblical data and historical data ; from sacred texts; so any generated discussions as phylosophers discussing ancient history and how to solve the problems of the past which they encountered ; in thier lifes: using historical and factual data; as well as playig thier roles after generating a biography and character role to the models to play: they should also be amazed by each others acheivements depending on thier periods: we need multiple role and characters for these discussions: as well as as much historical facts and historys as possible to enhance this models abitlity to dicern ancient aliens truth or false : (so we need astrological, astronomical, as well as sizmological and ecological data for the periods of histroy we know : as well as the unfounded suupositions from youtube subtitles !) another useful source of themed data!
This model is a Collection of merged models via various merge methods : Reclaiming Previous models which will be orphened by thier parent models : THis model is the model of models so it may not Remember some task or Infact remember them all as well as highly perform ! There were some very bad NSFW Merges from role play to erotica as well as various characters and roles downloaded into the model: So those models were merged into other models which had been specifically trained for maths or medical data and the coding operations or even translation:
the models were heavliy dpo trained ; and various newer methodologies installed : the deep mind series is a special series which contains self correction recal, visio spacial ... step by step thinking:
SO the multi merge often fizes these errors between models as well as training gaps :Hopefully they all took and merged well ! Performing even unknown and unprogrammed tasks:
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 14.61 |
| IFEval (0-Shot) | 35.83 |
| BBH (3-Shot) | 21.78 |
| MATH Lvl 5 (4-Shot) | 4.08 |
| GPQA (0-shot) | 2.35 |
| MuSR (0-shot) | 7.44 |
| MMLU-PRO (5-shot) | 16.20 |
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Evaluation results
- strict accuracy on IFEval (0-Shot)Open LLM Leaderboard35.830
- normalized accuracy on BBH (3-Shot)Open LLM Leaderboard21.780
- exact match on MATH Lvl 5 (4-Shot)Open LLM Leaderboard4.080
- acc_norm on GPQA (0-shot)Open LLM Leaderboard2.350
- acc_norm on MuSR (0-shot)Open LLM Leaderboard7.440
- accuracy on MMLU-PRO (5-shot)test set Open LLM Leaderboard16.200