Qwen
Collection
Alibaba Cloud-based models
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1081 items
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Updated
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merge
This is a merge of pre-trained language models created using mergekit.
Model details:
He'll be back... or something.
Quants can be found here:
https://huggingface.co/mradermacher/Robo-Gutenberg_V1.0-GGUF
https://huggingface.co/mradermacher/Robo-Gutenberg_V1.0-i1-GGUF
Merge Method
This model was merged using the TIES merge method using rombodawg/Rombos-LLM-V2.6-Qwen-14b as a base.
Models Merged
The following models were included in the merge:
Configuration
The following YAML configuration was used to produce this model:
models:
- model: rombodawg/Rombos-LLM-V2.6-Qwen-14b
#no parameters necessary for base model
- model: nbeerbower/Qwen2.5-Gutenberg-Doppel-14B
parameters:
density: 0.7
weight: 0.7
- model: huihui-ai/Qwen2.5-14B-Instruct-abliterated-v2
parameters:
density: 0.5
weight: 0.5
merge_method: ties
base_model: rombodawg/Rombos-LLM-V2.6-Qwen-14b
parameters:
normalize: false
int8_mask: true
dtype: float16
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 36.30 |
| IFEval (0-Shot) | 60.08 |
| BBH (3-Shot) | 50.29 |
| MATH Lvl 5 (4-Shot) | 21.30 |
| GPQA (0-shot) | 18.12 |
| MuSR (0-shot) | 19.20 |
| MMLU-PRO (5-shot) | 48.79 |
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Inference Providers
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This model is not currently available via any of the supported third-party Inference Providers, and
the model is not deployed on the HF Inference API.
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Evaluation results
- strict accuracy on IFEval (0-Shot)Open LLM Leaderboard60.080
- normalized accuracy on BBH (3-Shot)Open LLM Leaderboard50.290
- exact match on MATH Lvl 5 (4-Shot)Open LLM Leaderboard21.300
- acc_norm on GPQA (0-shot)Open LLM Leaderboard18.120
- acc_norm on MuSR (0-shot)Open LLM Leaderboard19.200
- accuracy on MMLU-PRO (5-shot)test set Open LLM Leaderboard48.790