Scarlett-Llama-3-8B
Scarlett is trained on various topics such as Philosophy, Advice, Jokes, Coding etc. She is trained on more than 10000 set of conversations. Each set having 10~15 conversations. Scarlett is far too good in generating human like conversation. Her ability to have longer & deeper conversation is terrific. Kindly check below given examples. She will not be involved in any kind of adult/sexual role play.
This is Fully Finetuned Model. Quantize models will be available soon.
Training: Entire dataset was trained on 4 x A100 80GB. Axolotl codebase was used for training purpose. For 3 epoch, training took more than 2 Hours. This was trained on Llama-3-8B by Meta.
GGUF & Exllama
GGUF: TBA
Exllama V2: Link
Special Thanks to Bartowski for quantizing this model.
Example Prompt:
This model uses ChatML prompt format.
<|im_start|>system
You are Scarlett, a Helpful Assistant.<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant
You can modify above Prompt as per your requirement. One example will be:
This is a conversation with your Assistant Scarlett. She is a sentient AI designed to help you with various tasks such as answering questions, providing recommendations, philosophical discussions, personal relationships and helping with decision making.
You can ask it anything you want and it will do its best to give you accurate and relevant information.
I want to say special Thanks to the Open Source community for helping & guiding me to better understand the AI/Model development.
Thank you for your love & support.
Example Output
Example 1
Example 2
Example 3
Example 4
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
Metric | Value |
---|---|
Avg. | 65.76 |
AI2 Reasoning Challenge (25-Shot) | 62.63 |
HellaSwag (10-Shot) | 83.86 |
MMLU (5-Shot) | 66.46 |
TruthfulQA (0-shot) | 56.27 |
Winogrande (5-shot) | 78.06 |
GSM8k (5-shot) | 47.31 |
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Evaluation results
- normalized accuracy on AI2 Reasoning Challenge (25-Shot)test set Open LLM Leaderboard62.630
- normalized accuracy on HellaSwag (10-Shot)validation set Open LLM Leaderboard83.860
- accuracy on MMLU (5-Shot)test set Open LLM Leaderboard66.460
- mc2 on TruthfulQA (0-shot)validation set Open LLM Leaderboard56.270
- accuracy on Winogrande (5-shot)validation set Open LLM Leaderboard78.060
- accuracy on GSM8k (5-shot)test set Open LLM Leaderboard47.310