Quantization made by Richard Erkhov.

IceLemonTeaRP-32k-7b - GGUF

Model creator: https://huggingface.co/icefog72/
Original model: https://huggingface.co/icefog72/IceLemonTeaRP-32k-7b/

Name	Quant method	Size
IceLemonTeaRP-32k-7b.Q2_K.gguf	Q2_K	2.53GB
IceLemonTeaRP-32k-7b.IQ3_XS.gguf	IQ3_XS	2.81GB
IceLemonTeaRP-32k-7b.IQ3_S.gguf	IQ3_S	2.96GB
IceLemonTeaRP-32k-7b.Q3_K_S.gguf	Q3_K_S	2.95GB
IceLemonTeaRP-32k-7b.IQ3_M.gguf	IQ3_M	3.06GB
IceLemonTeaRP-32k-7b.Q3_K.gguf	Q3_K	3.28GB
IceLemonTeaRP-32k-7b.Q3_K_M.gguf	Q3_K_M	3.28GB
IceLemonTeaRP-32k-7b.Q3_K_L.gguf	Q3_K_L	3.56GB
IceLemonTeaRP-32k-7b.IQ4_XS.gguf	IQ4_XS	3.67GB
IceLemonTeaRP-32k-7b.Q4_0.gguf	Q4_0	3.83GB
IceLemonTeaRP-32k-7b.IQ4_NL.gguf	IQ4_NL	3.87GB
IceLemonTeaRP-32k-7b.Q4_K_S.gguf	Q4_K_S	3.86GB
IceLemonTeaRP-32k-7b.Q4_K.gguf	Q4_K	4.07GB
IceLemonTeaRP-32k-7b.Q4_K_M.gguf	Q4_K_M	4.07GB
IceLemonTeaRP-32k-7b.Q4_1.gguf	Q4_1	4.24GB
IceLemonTeaRP-32k-7b.Q5_0.gguf	Q5_0	4.65GB
IceLemonTeaRP-32k-7b.Q5_K_S.gguf	Q5_K_S	4.65GB
IceLemonTeaRP-32k-7b.Q5_K.gguf	Q5_K	4.78GB
IceLemonTeaRP-32k-7b.Q5_K_M.gguf	Q5_K_M	4.78GB
IceLemonTeaRP-32k-7b.Q5_1.gguf	Q5_1	5.07GB
IceLemonTeaRP-32k-7b.Q6_K.gguf	Q6_K	5.53GB
IceLemonTeaRP-32k-7b.Q8_0.gguf	Q8_0	7.17GB

Original model description:

license: cc-by-nc-4.0 library_name: transformers tags: - mergekit - merge - alpaca - mistral - not-for-all-audiences - nsfw base_model: - icefog72/Kunokukulemonchini-32k-7b - icefog72/Mixtral_AI_Cyber_3.m1-BigL - grimjim/kukulemon-32K-7B - LeroyDyer/Mixtral_AI_Cyber_3.m1 - Nitral-AI/Kunocchini-7b-128k-test - Undi95/BigL-7B model-index: - name: IceLemonTeaRP-32k-7b results: - task: type: text-generation name: Text Generation dataset: name: AI2 Reasoning Challenge (25-Shot) type: ai2_arc config: ARC-Challenge split: test args: num_few_shot: 25 metrics: - type: acc_norm value: 67.66 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=icefog72/IceLemonTeaRP-32k-7b name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: HellaSwag (10-Shot) type: hellaswag split: validation args: num_few_shot: 10 metrics: - type: acc_norm value: 86.53 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=icefog72/IceLemonTeaRP-32k-7b name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: MMLU (5-Shot) type: cais/mmlu config: all split: test args: num_few_shot: 5 metrics: - type: acc value: 64.51 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=icefog72/IceLemonTeaRP-32k-7b name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: TruthfulQA (0-shot) type: truthful_qa config: multiple_choice split: validation args: num_few_shot: 0 metrics: - type: mc2 value: 61.76 source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=icefog72/IceLemonTeaRP-32k-7b name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: Winogrande (5-shot) type: winogrande config: winogrande_xl split: validation args: num_few_shot: 5 metrics: - type: acc value: 79.72 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=icefog72/IceLemonTeaRP-32k-7b name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: GSM8k (5-shot) type: gsm8k config: main split: test args: num_few_shot: 5 metrics: - type: acc value: 62.4 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=icefog72/IceLemonTeaRP-32k-7b name: Open LLM Leaderboard - 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: 52.12 name: strict accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=icefog72/IceLemonTeaRP-32k-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: 30.14 name: normalized accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=icefog72/IceLemonTeaRP-32k-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: 4.83 name: exact match source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=icefog72/IceLemonTeaRP-32k-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: 5.37 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=icefog72/IceLemonTeaRP-32k-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: 12.2 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=icefog72/IceLemonTeaRP-32k-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: 22.97 name: accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=icefog72/IceLemonTeaRP-32k-7b name: Open LLM Leaderboard

IceLemonTeaRP-32k-7b

This is a merge of pre-trained language models created using mergekit.

I would suggest to play with rope_theta in config.json to set between 40000-100000.

Merge Details

Cooked merge from fresh ingredients to fix icefog72/IceTeaRP-7b repetition problems.

Prompt template: Alpaca, maybe ChatML

measurement.json for quanting exl2 included.

Thanks for

Merge Method

This model was merged using the SLERP merge method.

Models Merged

The following models were included in the merge:

icefog72/Kunokukulemonchini-32k-7b
- grimjim/kukulemon-32K-7B
- Nitral-AI/Kunocchini-7b-128k-test
icefog72/Mixtral_AI_Cyber_3.m1-BigL
- LeroyDyer/Mixtral_AI_Cyber_3.m1
- Undi95/BigL-7B

How to download From the command line

I recommend using the huggingface-hub Python library:

pip3 install huggingface-hub

To download the main branch to a folder called IceLemonTeaRP-32k-7b:

mkdir IceLemonTeaRP-32k-7b
huggingface-cli download icefog72/IceLemonTeaRP-32k-7b --local-dir IceLemonTeaRP-32k-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.

To accelerate downloads on fast connections (1Gbit/s or higher), install hf_transfer:

pip3 install hf_transfer

And set environment variable HF_HUB_ENABLE_HF_TRANSFER to 1:

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.

### Configuration

The following YAML configuration was used to produce this model:


slices:
  - sources:
      - model: Mixtral_AI_Cyber_3.m1-BigL
        layer_range: [0, 32]
      - model: Kunokukulemonchini-32k-7b
        layer_range: [0, 32]
merge_method: slerp
base_model: Kunokukulemonchini-32k-7b
parameters:
  t:
    - filter: self_attn
      value: [0, 0.5, 0.3, 0.7, 1]
    - filter: mlp
      value: [1, 0.5, 0.7, 0.3, 0]
    - value: 0.5
dtype: float16

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	70.43
AI2 Reasoning Challenge (25-Shot)	67.66
HellaSwag (10-Shot)	86.53
MMLU (5-Shot)	64.51
TruthfulQA (0-shot)	61.76
Winogrande (5-shot)	79.72
GSM8k (5-shot)	62.40

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	21.27
IFEval (0-Shot)	52.12
BBH (3-Shot)	30.14
MATH Lvl 5 (4-Shot)	4.83
GPQA (0-shot)	5.37
MuSR (0-shot)	12.20
MMLU-PRO (5-shot)	22.97