Vision/multimodal capabilities:
If you want to use vision functionality:
- You must use the latest versions of Koboldcpp.
To use the multimodal capabilities of this model and use vision you need to load the specified mmproj file, this can be found inside this model repo.
- You can load the mmproj by using the corresponding section in the interface:
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
Metric | Value |
---|---|
Avg. | 69.79 |
AI2 Reasoning Challenge (25-Shot) | 67.58 |
HellaSwag (10-Shot) | 86.03 |
MMLU (5-Shot) | 64.79 |
TruthfulQA (0-shot) | 59.58 |
Winogrande (5-shot) | 79.64 |
GSM8k (5-shot) | 61.11 |
- Downloads last month
- 93
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Model tree for Nitral-AI/Stanta-Lelemon-Maid-7B
Spaces using Nitral-AI/Stanta-Lelemon-Maid-7B 6
Evaluation results
- normalized accuracy on AI2 Reasoning Challenge (25-Shot)test set Open LLM Leaderboard67.580
- normalized accuracy on HellaSwag (10-Shot)validation set Open LLM Leaderboard86.030
- accuracy on MMLU (5-Shot)test set Open LLM Leaderboard64.790
- mc2 on TruthfulQA (0-shot)validation set Open LLM Leaderboard59.580
- accuracy on Winogrande (5-shot)validation set Open LLM Leaderboard79.640
- accuracy on GSM8k (5-shot)test set Open LLM Leaderboard61.110