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--- |
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base_model: |
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- mistralai/Mixtral-8x7B-v0.1 |
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- mistralai/Mixtral-8x7B-v0.1 |
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- Doctor-Shotgun/limarp-zloss-mixtral-8x7b-qlora |
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- KoboldAI/Mixtral-8x7B-Holodeck-v1 |
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- jondurbin/bagel-dpo-8x7b-v0.2 |
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- mistralai/Mixtral-8x7B-Instruct-v0.1 |
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tags: |
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- mergekit |
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- merge |
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license: apache-2.0 |
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--- |
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# DonutHole-8x7B |
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[GGUF versions here](https://huggingface.co/ycros/DonutHole-8x7B-GGUF) |
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Bagel, Mixtral Instruct, Holodeck, LimaRP. |
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> What mysteries lie in the hole of a donut? |
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Good with Alpaca prompt formats, also works with Mistral format. See usage details below. |
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![image/webp](https://cdn-uploads.huggingface.co/production/uploads/63044fa07373aacccd8a7c53/VILuxGHvEPmDsn0YUX6Gh.webp) |
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This is similar to [BagelMIsteryTour](https://huggingface.co/ycros/BagelMIsteryTour-v2-8x7B), but I've swapped out Sensualize for the new Holodeck. |
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I'm not sure if it's better or not yet, or how it does at higher (8k+) contexts just yet. |
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Similar sampler advice applies as for BMT: minP (0.07 - 0.3 to taste) -> temp (either dynatemp 0-4ish, or like a temp of 3-4 with a smoothing factor of around 2.5ish). |
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And yes, that's temp last. It does okay without rep pen up to a point, it doesn't seem to get into a complete jam, but it can start to repeat sentences, |
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so you'll probably need some, perhaps 1.02-1.05 at a 1024 range seems okayish. |
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(rep pen sucks, but there are better things coming). |
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I've mainly tested with LimaRP style Alpaca prompts (instruction/input/response), and briefly with Mistral's own format. |
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**Full credit to all the model and dataset authors, I am but a derp with compute and a yaml file.** |
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--- |
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This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit). |
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## Merge Details |
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### Merge Method |
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This model was merged using the [DARE](https://arxiv.org/abs/2311.03099) [TIES](https://arxiv.org/abs/2306.01708) merge method using [mistralai/Mixtral-8x7B-v0.1](https://huggingface.co/mistralai/Mixtral-8x7B-v0.1) as a base. |
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### Models Merged |
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The following models were included in the merge: |
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* [mistralai/Mixtral-8x7B-v0.1](https://huggingface.co/mistralai/Mixtral-8x7B-v0.1) + [Doctor-Shotgun/limarp-zloss-mixtral-8x7b-qlora](https://huggingface.co/Doctor-Shotgun/limarp-zloss-mixtral-8x7b-qlora) |
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* [KoboldAI/Mixtral-8x7B-Holodeck-v1](https://huggingface.co/KoboldAI/Mixtral-8x7B-Holodeck-v1) |
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* [jondurbin/bagel-dpo-8x7b-v0.2](https://huggingface.co/jondurbin/bagel-dpo-8x7b-v0.2) |
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* [mistralai/Mixtral-8x7B-Instruct-v0.1](https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1) |
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### Configuration |
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The following YAML configuration was used to produce this model: |
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```yaml |
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base_model: mistralai/Mixtral-8x7B-v0.1 |
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models: |
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- model: mistralai/Mixtral-8x7B-v0.1+Doctor-Shotgun/limarp-zloss-mixtral-8x7b-qlora |
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parameters: |
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density: 0.5 |
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weight: 0.2 |
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- model: KoboldAI/Mixtral-8x7B-Holodeck-v1 |
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parameters: |
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density: 0.5 |
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weight: 0.2 |
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- model: mistralai/Mixtral-8x7B-Instruct-v0.1 |
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parameters: |
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density: 0.6 |
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weight: 1.0 |
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- model: jondurbin/bagel-dpo-8x7b-v0.2 |
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parameters: |
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density: 0.6 |
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weight: 0.5 |
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merge_method: dare_ties |
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dtype: bfloat16 |
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``` |