--- language: - en license: other tags: - art - philosophy - romance - jokes - advice - code - companionship license_name: llama3 license_link: LICENSE model-index: - name: Scarlett-Llama-3-8B results: - task: type: text-generation name: Text Generation dataset: name: AI2 Reasoning Challenge (25-Shot) type: ai2_arc config: ARC-Challenge split: test args: num_few_shot: 25 metrics: - type: acc_norm value: 62.63 name: normalized accuracy source: url: >- https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ajibawa-2023/Scarlett-Llama-3-8B name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: HellaSwag (10-Shot) type: hellaswag split: validation args: num_few_shot: 10 metrics: - type: acc_norm value: 83.86 name: normalized accuracy source: url: >- https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ajibawa-2023/Scarlett-Llama-3-8B name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: MMLU (5-Shot) type: cais/mmlu config: all split: test args: num_few_shot: 5 metrics: - type: acc value: 66.46 name: accuracy source: url: >- https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ajibawa-2023/Scarlett-Llama-3-8B name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: TruthfulQA (0-shot) type: truthful_qa config: multiple_choice split: validation args: num_few_shot: 0 metrics: - type: mc2 value: 56.27 source: url: >- https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ajibawa-2023/Scarlett-Llama-3-8B name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: Winogrande (5-shot) type: winogrande config: winogrande_xl split: validation args: num_few_shot: 5 metrics: - type: acc value: 78.06 name: accuracy source: url: >- https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ajibawa-2023/Scarlett-Llama-3-8B name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: GSM8k (5-shot) type: gsm8k config: main split: test args: num_few_shot: 5 metrics: - type: acc value: 47.31 name: accuracy source: url: >- https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ajibawa-2023/Scarlett-Llama-3-8B name: Open LLM Leaderboard --- **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](https://huggingface.co/bartowski/Scarlett-Llama-3-8B-exl2) Special Thanks to [Bartowski](https://huggingface.co/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 ![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/64aea8ff67511bd3d965697b/CJP33lf4w-ltFQ89Twbra.jpeg) Example 2 ![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/64aea8ff67511bd3d965697b/1P1B5MVLFkJGFAjX587Zh.jpeg) Example 3 ![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/64aea8ff67511bd3d965697b/0w_w325BCUP8Cov09QFgf.jpeg) Example 4 ![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/64aea8ff67511bd3d965697b/mrtCrVpGCk_qXz-RCArGm.jpeg) # [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_ajibawa-2023__Scarlett-Llama-3-8B) | 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|