--- license: cc-by-nc-4.0 library_name: transformers tags: - mergekit - merge - alpaca - mistral - not-for-all-audiences - nsfw base_model: - icefog72/IceCoffeeRP-7b - icefog72/IceBlendedLatteRP-7b - eldogbbhed/NeuralBeagleJaskier model-index: - name: IceCocoaRP-7b results: - task: type: text-generation name: Text Generation dataset: name: IFEval (0-Shot) type: HuggingFaceH4/ifeval args: num_few_shot: 0 metrics: - type: inst_level_strict_acc and prompt_level_strict_acc value: 49.62 name: strict accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=icefog72/IceCocoaRP-7b name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: BBH (3-Shot) type: BBH args: num_few_shot: 3 metrics: - type: acc_norm value: 29.64 name: normalized accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=icefog72/IceCocoaRP-7b name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: MATH Lvl 5 (4-Shot) type: hendrycks/competition_math args: num_few_shot: 4 metrics: - type: exact_match value: 5.44 name: exact match source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=icefog72/IceCocoaRP-7b name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: GPQA (0-shot) type: Idavidrein/gpqa args: num_few_shot: 0 metrics: - type: acc_norm value: 6.04 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=icefog72/IceCocoaRP-7b name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: MuSR (0-shot) type: TAUR-Lab/MuSR args: num_few_shot: 0 metrics: - type: acc_norm value: 11.17 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=icefog72/IceCocoaRP-7b name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: MMLU-PRO (5-shot) type: TIGER-Lab/MMLU-Pro config: main split: test args: num_few_shot: 5 metrics: - type: acc value: 23.32 name: accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=icefog72/IceCocoaRP-7b name: Open LLM Leaderboard --- # IceCocoaRP-7b ![image/png](https://cdn-uploads.huggingface.co/production/uploads/63407b719dbfe0d48b2d763b/AN1QDxVIoxzk965qzRxOB.png) This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit). [SillyTavern Discord thread](https://discord.com/channels/1100685673633153084/1248929887570628688) [Rules-lorebook and settings I'm using you can find here](https://huggingface.co/icefog72/GeneralInfoToStoreNotModel/tree/main) [ko-fi](https://ko-fi.com/icefog72) ## Merge Details The best one so far for me. - [4.2bpw-exl2](https://huggingface.co/icefog72/IceCocoaRP-7b-4.2bpw-exl2) - [6.5bpw-exl2](https://huggingface.co/icefog72/IceCocoaRP-7b-6.5bpw-exl2) - [8bpw-exl2](https://huggingface.co/icefog72/IceCocoaRP-7b-8bpw-exl2) thx mradermacher for - [GGUF](https://huggingface.co/mradermacher/IceCocoaRP-7b-GGUF) - [i1-GGUF](https://huggingface.co/mradermacher/IceCocoaRP-7b-i1-GGUF) ### Merge Method This model was merged using the [TIES](https://arxiv.org/abs/2306.01708) merge method using NeuralBeagleJaskier as a base. ### Models Merged The following models were included in the merge: * NeuralBeagleJaskier * IceBlendedCoffeeRP-7b (slerp bfloat16) - IceCoffeeRP-7b - IceBlendedLatteRP-7b base ### Configuration The following YAML configuration was used to produce this model: I recommend using the `huggingface-hub` Python library: ```shell pip3 install huggingface-hub ``` To download the `main` branch to a folder called `IceCocoaRP-7b`: ```shell mkdir IceCocoaRP-7b huggingface-cli download icefog72/IceCocoaRP-7b --local-dir IceCocoaRP-7b --local-dir-use-symlinks False ```
More advanced huggingface-cli download usage If you remove the `--local-dir-use-symlinks False` parameter, the files will instead be stored in the central Hugging Face cache directory (default location on Linux is: `~/.cache/huggingface`), and symlinks will be added to the specified `--local-dir`, pointing to their real location in the cache. This allows for interrupted downloads to be resumed, and allows you to quickly clone the repo to multiple places on disk without triggering a download again. The downside, and the reason why I don't list that as the default option, is that the files are then hidden away in a cache folder and it's harder to know where your disk space is being used, and to clear it up if/when you want to remove a download model. The cache location can be changed with the `HF_HOME` environment variable, and/or the `--cache-dir` parameter to `huggingface-cli`. For more documentation on downloading with `huggingface-cli`, please see: [HF -> Hub Python Library -> Download files -> Download from the CLI](https://huggingface.co/docs/huggingface_hub/guides/download#download-from-the-cli). To accelerate downloads on fast connections (1Gbit/s or higher), install `hf_transfer`: ```shell pip3 install hf_transfer ``` And set environment variable `HF_HUB_ENABLE_HF_TRANSFER` to `1`: ```shell mkdir FOLDERNAME HF_HUB_ENABLE_HF_TRANSFER=1 huggingface-cli download MODEL --local-dir FOLDERNAME --local-dir-use-symlinks False ``` Windows Command Line users: You can set the environment variable by running `set HF_HUB_ENABLE_HF_TRANSFER=1` before the download command.
```yaml models: - model: NeuralBeagleJaskier parameters: density: 0.9 weight: 0.5 - model: IceBlendedCoffeeRP-7b parameters: density: 0.5 weight: 0.3 merge_method: ties base_model: NeuralBeagleJaskier parameters: normalize: true int8_mask: true dtype: float16 ``` # [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard) Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_icefog72__IceCocoaRP-7b) | Metric |Value| |-------------------|----:| |Avg. |20.87| |IFEval (0-Shot) |49.62| |BBH (3-Shot) |29.64| |MATH Lvl 5 (4-Shot)| 5.44| |GPQA (0-shot) | 6.04| |MuSR (0-shot) |11.17| |MMLU-PRO (5-shot) |23.32|