Supernova
Collection
Stable and tested series of models • 3 items • Updated
output = llm(
"Once upon a time,",
max_tokens=512,
echo=True
)
print(output)Supernova-experimental
Quantized to GGUF using llama.cpp
This is an experimental model that was created for the development of NovaAI.
Good at chatting and some RP.
Prompt Template: Alpaca
Below is an instruction that describes a task. Write a response that appropriately completes the request.
### Instruction:
{prompt}
### Response:
Models Merged
The following models were included in the merge:
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 59.79 |
| AI2 Reasoning Challenge (25-Shot) | 63.05 |
| HellaSwag (10-Shot) | 83.66 |
| MMLU (5-Shot) | 56.59 |
| TruthfulQA (0-shot) | 49.37 |
| Winogrande (5-shot) | 77.35 |
| GSM8k (5-shot) | 28.73 |
- Downloads last month
- 30
Hardware compatibility
Log In to add your hardware
3-bit
4-bit
5-bit
6-bit
8-bit
16-bit
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support
Model tree for theNovaAI/Supernova-experimental-GGUF
Collection including theNovaAI/Supernova-experimental-GGUF
Evaluation results
- normalized accuracy on AI2 Reasoning Challenge (25-Shot)test set Open LLM Leaderboard63.050
- normalized accuracy on HellaSwag (10-Shot)validation set Open LLM Leaderboard83.660
- accuracy on MMLU (5-Shot)test set Open LLM Leaderboard56.590
- mc2 on TruthfulQA (0-shot)validation set Open LLM Leaderboard49.370
- accuracy on Winogrande (5-shot)validation set Open LLM Leaderboard77.350
- accuracy on GSM8k (5-shot)test set Open LLM Leaderboard28.730
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="theNovaAI/Supernova-experimental-GGUF", filename="", )