Quantization made by Richard Erkhov.

Infinite-Laymons-9B - GGUF

Model creator: https://huggingface.co/ABX-AI/
Original model: https://huggingface.co/ABX-AI/Infinite-Laymons-9B/

Name	Quant method	Size
Infinite-Laymons-9B.Q2_K.gguf	Q2_K	3.13GB
Infinite-Laymons-9B.IQ3_XS.gguf	IQ3_XS	3.48GB
Infinite-Laymons-9B.IQ3_S.gguf	IQ3_S	3.67GB
Infinite-Laymons-9B.Q3_K_S.gguf	Q3_K_S	3.65GB
Infinite-Laymons-9B.IQ3_M.gguf	IQ3_M	3.79GB
Infinite-Laymons-9B.Q3_K.gguf	Q3_K	4.05GB
Infinite-Laymons-9B.Q3_K_M.gguf	Q3_K_M	4.05GB
Infinite-Laymons-9B.Q3_K_L.gguf	Q3_K_L	4.41GB
Infinite-Laymons-9B.IQ4_XS.gguf	IQ4_XS	4.55GB
Infinite-Laymons-9B.Q4_0.gguf	Q4_0	4.74GB
Infinite-Laymons-9B.IQ4_NL.gguf	IQ4_NL	4.79GB
Infinite-Laymons-9B.Q4_K_S.gguf	Q4_K_S	4.78GB
Infinite-Laymons-9B.Q4_K.gguf	Q4_K	5.04GB
Infinite-Laymons-9B.Q4_K_M.gguf	Q4_K_M	5.04GB
Infinite-Laymons-9B.Q4_1.gguf	Q4_1	5.26GB
Infinite-Laymons-9B.Q5_0.gguf	Q5_0	5.77GB
Infinite-Laymons-9B.Q5_K_S.gguf	Q5_K_S	5.77GB
Infinite-Laymons-9B.Q5_K.gguf	Q5_K	5.93GB
Infinite-Laymons-9B.Q5_K_M.gguf	Q5_K_M	5.93GB
Infinite-Laymons-9B.Q5_1.gguf	Q5_1	6.29GB
Infinite-Laymons-9B.Q6_K.gguf	Q6_K	6.87GB
Infinite-Laymons-9B.Q8_0.gguf	Q8_0	8.89GB

Original model description:

license: other library_name: transformers tags: - mergekit - merge - not-for-all-audiences base_model: - Nitral-AI/Infinitely-Laydiculous-7B model-index: - name: Infinite-Laymons-9B 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: 65.61 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ABX-AI/Infinite-Laymons-9B 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: 84.14 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ABX-AI/Infinite-Laymons-9B 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: 64.53 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ABX-AI/Infinite-Laymons-9B 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: 54.87 source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ABX-AI/Infinite-Laymons-9B 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: 80.82 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ABX-AI/Infinite-Laymons-9B 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: 53.75 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ABX-AI/Infinite-Laymons-9B name: Open LLM Leaderboard

Infinite-Laymons-9B

Infinite-Laymons-9B is intended for fictional role-play and storytelling.

The focus is on original responses and elimitation, or reduction of refusals.

GGUF / IQ / Imatrix

Merge Details

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

Merge Method

This model was merged using the passthrough merge method.

Models Merged

The following models were included in the merge:

Configuration

The following YAML configuration was used to produce this model:

slices:
  - sources:
      - model: Nitral-AI/Infinitely-Laydiculous-7B
        layer_range: [0, 20]
  - sources:
      - model: ABX-AI/Infinite-Laymons-7B
        layer_range: [12, 32]
merge_method: passthrough
dtype: float16

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	67.29
AI2 Reasoning Challenge (25-Shot)	65.61
HellaSwag (10-Shot)	84.14
MMLU (5-Shot)	64.53
TruthfulQA (0-shot)	54.87
Winogrande (5-shot)	80.82
GSM8k (5-shot)	53.75