Seraph-7B
This is the model for Seraph-7B. I used mergekit to merge models.
Prompt Templates
You can use these prompt templates, but I recommend using ChatML.
ChatML:
<|im_start|>system
{system}<|im_end|>
<|im_start|>user
{user}<|im_end|>
<|im_start|>assistant
{asistant}<|im_end|>
System, User, Asistant Alpaca Style:
### System:
{system}
### User:
{user}
### Assistant:
Yaml Config
slices:
- sources:
- model: Weyaxi/OpenHermes-2.5-neural-chat-v3-3-Slerp
layer_range: [0, 32]
- model: Q-bert/MetaMath-Cybertron-Starling
layer_range: [0, 32]
merge_method: slerp
base_model: mistralai/Mistral-7B-v0.1
parameters:
t:
- filter: self_attn
value: [0, 0.5, 0.3, 0.7, 1]
- filter: mlp
value: [1, 0.5, 0.7, 0.3, 0]
- value: 0.5 # fallback for rest of tensors
dtype: bfloat16
Quantizationed versions
Quantizationed versions of this model is available thanks to TheBloke.
GPTQ
GGUF
AWQ
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
Metric | Value |
---|---|
Avg. | 71.86 |
ARC (25-shot) | 67.83 |
HellaSwag (10-shot) | 86.22 |
MMLU (5-shot) | 65.07 |
TruthfulQA (0-shot) | 59.49 |
Winogrande (5-shot) | 80.66 |
GSM8K (5-shot) | 71.87 |
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Evaluation results
- normalized accuracy on AI2 Reasoning Challenge (25-Shot)test set Open LLM Leaderboard67.830
- normalized accuracy on HellaSwag (10-Shot)validation set Open LLM Leaderboard86.220
- accuracy on MMLU (5-Shot)test set Open LLM Leaderboard65.070
- mc2 on TruthfulQA (0-shot)validation set Open LLM Leaderboard59.490
- accuracy on Winogrande (5-shot)validation set Open LLM Leaderboard80.660
- accuracy on GSM8k (5-shot)test set Open LLM Leaderboard71.870