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--- |
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license: apache-2.0 |
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tags: |
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- moe |
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- merge |
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- mergekit |
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- Solar Moe |
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- Solar |
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- Lumosia |
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model-index: |
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- name: Lumosia-MoE-4x10.7 |
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results: |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: AI2 Reasoning Challenge (25-Shot) |
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type: ai2_arc |
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config: ARC-Challenge |
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split: test |
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args: |
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num_few_shot: 25 |
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metrics: |
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- type: acc_norm |
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value: 68.34 |
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name: normalized accuracy |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Steelskull/Lumosia-MoE-4x10.7 |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: HellaSwag (10-Shot) |
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type: hellaswag |
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split: validation |
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args: |
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num_few_shot: 10 |
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metrics: |
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- type: acc_norm |
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value: 87.13 |
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name: normalized accuracy |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Steelskull/Lumosia-MoE-4x10.7 |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: MMLU (5-Shot) |
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type: cais/mmlu |
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config: all |
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split: test |
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args: |
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num_few_shot: 5 |
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metrics: |
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- type: acc |
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value: 64.38 |
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name: accuracy |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Steelskull/Lumosia-MoE-4x10.7 |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: TruthfulQA (0-shot) |
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type: truthful_qa |
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config: multiple_choice |
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split: validation |
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args: |
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num_few_shot: 0 |
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metrics: |
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- type: mc2 |
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value: 63.81 |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Steelskull/Lumosia-MoE-4x10.7 |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: Winogrande (5-shot) |
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type: winogrande |
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config: winogrande_xl |
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split: validation |
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args: |
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num_few_shot: 5 |
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metrics: |
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- type: acc |
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value: 82.95 |
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name: accuracy |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Steelskull/Lumosia-MoE-4x10.7 |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: GSM8k (5-shot) |
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type: gsm8k |
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config: main |
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split: test |
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args: |
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num_few_shot: 5 |
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metrics: |
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- type: acc |
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value: 51.02 |
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name: accuracy |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Steelskull/Lumosia-MoE-4x10.7 |
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name: Open LLM Leaderboard |
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--- |
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 |
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# Lumosia-MoE-4x10.7 |
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|
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"Lumosia" was selected as its a MoE of Multiple SOLAR Merges so it really "Lights the way".... its 3am. |
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This is a very experimantal model. its a MoE of all good performing Solar models (based off of personal experiance not open leaderboard), |
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The models goal was to make a good all rounder, in chat/logic/rp |
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Why? Dunno whated to see what would happen |
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context is 4k but coherent up to 16k |
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Quants by @thebloke (thank you) |
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https://huggingface.co/TheBloke/Lumosia-MoE-4x10.7-GGUF |
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https://huggingface.co/TheBloke/Lumosia-MoE-4x10.7-GPTQ |
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Update: (Done) |
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Lumosia v1.5 has been uploaded. |
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Update 2: |
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A Lumosia Personality tavern card has been added |
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Template: |
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``` |
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### System: |
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### USER:{prompt} |
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### Assistant: |
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``` |
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Settings: |
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``` |
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Temp: 1.0 |
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min-p: 0.02-0.1 |
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``` |
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Lumosia-MoE-4x10.7 is a Mixure of Experts (MoE) made with the following models: |
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* [DopeorNope/SOLARC-M-10.7B](https://huggingface.co/DopeorNope/SOLARC-M-10.7B) |
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* [maywell/PiVoT-10.7B-Mistral-v0.2-RP](https://huggingface.co/maywell/PiVoT-10.7B-Mistral-v0.2-RP) |
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* [kyujinpy/Sakura-SOLAR-Instruct](https://huggingface.co/kyujinpy/Sakura-SOLAR-Instruct) |
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* [jeonsworld/CarbonVillain-en-10.7B-v1](https://huggingface.co/jeonsworld/CarbonVillain-en-10.7B-v1) |
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## Evals: |
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|
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* Avg: 69.61 |
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* ARC: 68.34 |
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* HellaSwag: 87.13 |
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* MMLU: 64.38 |
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* T-QA: 63.81 |
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* Winogrande: 82.95 |
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* GSM8K: 51.02 |
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## Examples: |
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``` |
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Example 1: |
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User: |
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Hello lumi, what is the meaning of life |
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in around 100 words. |
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Lumosia: |
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The meaning of life can vary greatly |
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depending on individual beliefs, |
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values, and experiences. One common |
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perspective suggests that the primary |
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purpose of life is to seek happiness, |
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fulfillment, and personal growth |
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through relationships |
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accomplishments, and spiritual |
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awareness. Living with integrity. |
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compassion, and gratitude while |
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making a positive impact on others |
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and the world around us can also |
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contribute to finding meaning in life |
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UItimately, the meaning of life is |
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subjective and unique to each |
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individual, who must define it for |
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themselves through exploration |
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reflection, and personal choice. |
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``` |
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``` |
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Example 2: |
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User: |
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Explain a MoE (Mixture of Experts) in |
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around 100 words |
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Lumosia: |
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A MoE, short for Mixture of Experts, is |
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a machine learning technique utilized |
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in ensemble learning. It involves |
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combining multiple specialist models |
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(experts) to optimize predictive |
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performance. Each expert focuses on |
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a subset of the input features or data |
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domains, making them specialized in |
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particular areas. Through a weighting |
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mechanism, like Gaussian Mixture |
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Model, the predictions of experts are |
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blended to produce a final result. MoE |
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models demonstrate effectiveness in |
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handling complex or ambiguous |
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inputs where a single model might |
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struggle. They are commonly used in |
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natural language processing. |
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computer vision, and speech synthesis. |
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``` |
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## 🧩 Configuration |
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|
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``` |
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yamlbase_model: DopeorNope/SOLARC-M-10.7B |
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gate_mode: hidden |
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dtype: bfloat16 |
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experts: |
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- source_model: DopeorNope/SOLARC-M-10.7B |
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positive_prompts: [""] |
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- source_model: maywell/PiVoT-10.7B-Mistral-v0.2-RP |
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positive_prompts: [""] |
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- source_model: kyujinpy/Sakura-SOLAR-Instruct |
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positive_prompts: [""] |
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- source_model: jeonsworld/CarbonVillain-en-10.7B-v1 |
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positive_prompts: [""] |
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``` |
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|
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## 💻 Usage |
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|
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``` |
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python |
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!pip install -qU transformers bitsandbytes accelerate |
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|
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from transformers import AutoTokenizer |
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import transformers |
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import torch |
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model = "Steelskull/Lumosia-MoE-4x10.7" |
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tokenizer = AutoTokenizer.from_pretrained(model) |
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pipeline = transformers.pipeline( |
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"text-generation", |
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model=model, |
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model_kwargs={"torch_dtype": torch.float16, "load_in_4bit": True}, |
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) |
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messages = [{"role": "user", "content": "Explain what a Mixture of Experts is in less than 100 words."}] |
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prompt = pipeline.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True) |
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outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95) |
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print(outputs[0]["generated_text"]) |
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``` |
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# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard) |
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Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_Steelskull__Lumosia-MoE-4x10.7) |
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|
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| Metric |Value| |
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|---------------------------------|----:| |
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|Avg. |69.61| |
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|AI2 Reasoning Challenge (25-Shot)|68.34| |
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|HellaSwag (10-Shot) |87.13| |
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|MMLU (5-Shot) |64.38| |
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|TruthfulQA (0-shot) |63.81| |
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|Winogrande (5-shot) |82.95| |
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|GSM8k (5-shot) |51.02| |
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