Text Generation
Transformers
PyTorch
llama
Not-For-All-Audiences
nsfw
text-generation-inference
Inference Endpoints
license: cc-by-nc-4.0 | |
tags: | |
- not-for-all-audiences | |
- nsfw | |
[HIGHLY EXPERIMENTAL] | |
Just try it for a good laugh. Need testing. | |
```shell | |
The plan : | |
Open-Orca/OpenOrcaxOpenChat-Preview2-13B | |
PygmalionAI/pygmalion-2-13b | |
Undi95/MLewd-L2-13B-v2-3 | |
jondurbin/spicyboros-13b-2.2 | |
lemonilia/limarp-llama2-v2 | |
Step 1: Merge OpenOrcaxOpenChat-Preview2-13B with pygmalion-2-13b | |
=> OpenOrcaPyg2 | |
Step 2: Merge MLewd with Spicyboros | |
=> MLewdBorosPlus | |
Step 3: In the layer side, replace the layer 0 to 8 with MLewd, and the layer 16 to 20 with Spicyboros of the first merge | |
=> OpenOrcaPyg2-Layered | |
Step 4: In the layer side, replace the layer 0 to 8 with MLewd, and the layer 16 to 20 with Spicyboros of the second merge | |
=> MLewdBorosPlus-Layered | |
Step 5: Merge OpenOrcaPyg2-Layered with MLewdBorosPlus-Layered | |
=> OpenRPBase | |
Step 6: Apply Limarp2 at 0.5 weight at the end | |
=> OpenRP | |
Goal: making Orca a RP model with Pyg2 dataset and MLewd+Spicyboros 100% layer accross the merge and avoid censoring | |
It will be diluted to ~25% in other layer, SLERP do the dirty job | |
The LoRA is here to redirect to RP writing | |
``` | |
Don't ask me why this model work. I'm a blind scientist. It seems a little obsessed with the game "Garry's mod" tho. Be patient with him. | |
SuperCOT applied : https://huggingface.co/Undi95/OpenRP-13B-SuperCOT | |
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard) | |
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_Undi95__OpenRP-13B) | |
| Metric | Value | | |
|-----------------------|---------------------------| | |
| Avg. | 53.25 | | |
| ARC (25-shot) | 62.12 | | |
| HellaSwag (10-shot) | 82.6 | | |
| MMLU (5-shot) | 57.5 | | |
| TruthfulQA (0-shot) | 48.29 | | |
| Winogrande (5-shot) | 76.01 | | |
| GSM8K (5-shot) | 12.89 | | |
| DROP (3-shot) | 33.38 | | |