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--- |
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license: llama2 |
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datasets: |
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- databricks/databricks-dolly-15k |
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language: |
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- en |
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pipeline_tag: text-generation |
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--- |
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# Instruct_Llama70B_Dolly15k |
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Fine-tuned from Llama-2-70B，used Dolly15k for the dataset. 80% for training, 15% validation, 5% test. Trained for 1.5 epochs using QLora. Trained with 1024 context window. |
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# Model Details |
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* **Trained by**: trained by [Brillibits](https://www.youtube.com/channel/UCAq9THVHhPK0Zv4Xi-88Jmg). |
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* **Model type:** **Instruct_Llama70B_Dolly15k** is an auto-regressive language model based on the Llama 2 transformer architecture. |
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* **Language(s)**: English |
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* **License for Instruct_Llama70B_Dolly15ks**: llama2 license |
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# Prompting |
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## Prompt Template With Context |
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``` |
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Write a 10-line poem about a given topic |
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Input: |
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The topic is about racecars |
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Output: |
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``` |
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## Prompt Template Without Context |
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``` |
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Who was the was the second president of the United States? |
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Output: |
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``` |
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## Professional Assistance |
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This model and other models like it are great, but where LLMs hold the most promise is when they are applied on custom data to automate a wide variety of tasks |
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If you have a dataset and want to see if you might be able to apply that data to automate some tasks, and you are looking for professional assistance, contact me [here](mailto:[email protected]) |
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# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard) |
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Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_Brillibits__Instruct_Llama70B_Dolly15k) |
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| Metric | Value | |
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|-----------------------|---------------------------| |
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| Avg. | 60.97 | |
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| ARC (25-shot) | 68.34 | |
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| HellaSwag (10-shot) | 87.21 | |
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| MMLU (5-shot) | 69.52 | |
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| TruthfulQA (0-shot) | 46.46 | |
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| Winogrande (5-shot) | 84.29 | |
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| GSM8K (5-shot) | 42.68 | |
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| DROP (3-shot) | 28.26 | |
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