Configuration Parsing
Warning:
In config.json: "quantization_config.bits" must be an integer
Exllamav2 quant (exl2 / 3.75 bpw) made with ExLlamaV2 v0.1.3
Other EXL2 quants:
Quant | Model Size | lm_head |
---|---|---|
Chunky-Lemon-Cookie-11B
This is a merge of pre-trained language models created using mergekit.
GGUF quants:
- https://huggingface.co/backyardai/Chunky-Lemon-Cookie-11B-GGUF
- https://huggingface.co/mradermacher/Chunky-Lemon-Cookie-11B-GGUF
Merge Details
Merge Method
This model was merged using the following methods:
- passthrough
- task arithmetic
Models Merged
The following models were included in the merge:
- SanjiWatsuki/Kunoichi-7B
- SanjiWatsuki/Silicon-Maid-7B
- KatyTheCutie/LemonadeRP-4.5.3
- Sao10K/Fimbulvetr-11B-v2
- mistralai/Mistral-7B-v0.1
Configuration
The following YAML configurations were used to produce this model:
slices:
- sources:
- model: mistralai/Mistral-7B-v0.1
layer_range: [0, 24]
- sources:
- model: mistralai/Mistral-7B-v0.1
layer_range: [8, 32]
merge_method: passthrough
dtype: float16
name: Mistral-11B
---
slices:
- sources:
- model: SanjiWatsuki/Kunoichi-7B
layer_range: [0, 24]
- sources:
- model: SanjiWatsuki/Silicon-Maid-7B
layer_range: [8, 24]
- sources:
- model: KatyTheCutie/LemonadeRP-4.5.3
layer_range: [24, 32]
merge_method: passthrough
dtype: float16
name: Big-Lemon-Cookie-11B
---
models:
- model: Big-Lemon-Cookie-11B
parameters:
weight: 0.85
- model: Sao10K/Fimbulvetr-11B-v2
parameters:
weight: 0.15
merge_method: task_arithmetic
base_model: Mistral-11B
dtype: float16
name: Chunky-Lemon-Cookie-11B
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
Metric | Value |
---|---|
Avg. | 70.23 |
AI2 Reasoning Challenge (25-Shot) | 69.62 |
HellaSwag (10-Shot) | 86.55 |
MMLU (5-Shot) | 65.35 |
TruthfulQA (0-shot) | 61.59 |
Winogrande (5-shot) | 79.79 |
GSM8k (5-shot) | 58.45 |
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Evaluation results
- normalized accuracy on AI2 Reasoning Challenge (25-Shot)test set Open LLM Leaderboard69.620
- normalized accuracy on HellaSwag (10-Shot)validation set Open LLM Leaderboard86.550
- accuracy on MMLU (5-Shot)test set Open LLM Leaderboard65.350
- mc2 on TruthfulQA (0-shot)validation set Open LLM Leaderboard61.590
- accuracy on Winogrande (5-shot)validation set Open LLM Leaderboard79.790
- accuracy on GSM8k (5-shot)test set Open LLM Leaderboard58.450