You can deploy this model and start earning money today!

RichardErkhov/
zelk12_-_MT-Gen1-gemma-2-9B-gguf

Name: zelk12_-_MT-Gen1-gemma-2-9B-gguf
Availability: InStock

Views

No views yet

Quantization made by Richard Erkhov.

Github

Discord

Request more models

MT-Gen1-gemma-2-9B - GGUF

Model creator: https://huggingface.co/zelk12/
Original model: https://huggingface.co/zelk12/MT-Gen1-gemma-2-9B/

Name	Quant method	Size
MT-Gen1-gemma-2-9B.Q2_K.gguf	Q2_K	3.54GB
MT-Gen1-gemma-2-9B.IQ3_XS.gguf	IQ3_XS	3.86GB
MT-Gen1-gemma-2-9B.IQ3_S.gguf	IQ3_S	4.04GB
MT-Gen1-gemma-2-9B.Q3_K_S.gguf	Q3_K_S	4.04GB
MT-Gen1-gemma-2-9B.IQ3_M.gguf	IQ3_M	4.19GB
MT-Gen1-gemma-2-9B.Q3_K.gguf	Q3_K	4.43GB
MT-Gen1-gemma-2-9B.Q3_K_M.gguf	Q3_K_M	4.43GB
MT-Gen1-gemma-2-9B.Q3_K_L.gguf	Q3_K_L	4.78GB
MT-Gen1-gemma-2-9B.IQ4_XS.gguf	IQ4_XS	4.86GB
MT-Gen1-gemma-2-9B.Q4_0.gguf	Q4_0	5.07GB
MT-Gen1-gemma-2-9B.IQ4_NL.gguf	IQ4_NL	5.1GB
MT-Gen1-gemma-2-9B.Q4_K_S.gguf	Q4_K_S	5.1GB
MT-Gen1-gemma-2-9B.Q4_K.gguf	Q4_K	5.37GB
MT-Gen1-gemma-2-9B.Q4_K_M.gguf	Q4_K_M	5.37GB
MT-Gen1-gemma-2-9B.Q4_1.gguf	Q4_1	5.55GB
MT-Gen1-gemma-2-9B.Q5_0.gguf	Q5_0	6.04GB
MT-Gen1-gemma-2-9B.Q5_K_S.gguf	Q5_K_S	6.04GB
MT-Gen1-gemma-2-9B.Q5_K.gguf	Q5_K	6.19GB
MT-Gen1-gemma-2-9B.Q5_K_M.gguf	Q5_K_M	6.19GB
MT-Gen1-gemma-2-9B.Q5_1.gguf	Q5_1	6.52GB
MT-Gen1-gemma-2-9B.Q6_K.gguf	Q6_K	7.07GB
MT-Gen1-gemma-2-9B.Q8_0.gguf	Q8_0	9.15GB

Original model description:

library_name: transformers tags:

mergekit
merge base_model:
zelk12/MT-Gen1-IG-gemma-2-9B
zelk12/MT-Gen1-MAMMMUB-gemma-2-9B model-index:
name: MT-Gen1-gemma-2-9B 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: 78.86 name: strict accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=zelk12/MT-Gen1-gemma-2-9B 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: 44.01 name: normalized accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=zelk12/MT-Gen1-gemma-2-9B 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: 12.08 name: exact match source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=zelk12/MT-Gen1-gemma-2-9B 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: 12.86 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=zelk12/MT-Gen1-gemma-2-9B 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: 11.58 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=zelk12/MT-Gen1-gemma-2-9B 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: 37.56 name: accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=zelk12/MT-Gen1-gemma-2-9B name: Open LLM Leaderboard

merge

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

Merge Details

Merge Method

This model was merged using the SLERP merge method.

Models Merged

The following models were included in the merge:

Configuration

The following YAML configuration was used to produce this model:

yaml

models:
  - model: zelk12/MT-Gen1-IG-gemma-2-9B
  - model: zelk12/MT-Gen1-MAMMMUB-gemma-2-9B
merge_method: slerp
base_model: zelk12/MT-Gen1-IG-gemma-2-9B
dtype: bfloat16
parameters:
  t: 0.666666667

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	32.83
IFEval (0-Shot)	78.86
BBH (3-Shot)	44.01
MATH Lvl 5 (4-Shot)	12.08
GPQA (0-shot)	12.86
MuSR (0-shot)	11.58
MMLU-PRO (5-shot)	37.56

RichardErkhov/zelk12_-_MT-Gen1-gemma-2-9B-gguf