
Minimal Alpaca-LORA trained with [databricks/databricks-dolly-v2-15k](https://huggingface.co/datasets/databricks/databricks-dolly-15k) dataset and based on [OpenLLaMA-3B-600BT](https://huggingface.co/openlm-research/open_llama_3b_600bt_preview).

There is a pre-trained LoRA adapter and a [Colab Jupyter notebook](https://colab.research.google.com/#fileId=https://huggingface.co/Sovenok-Hacker/openalpaca-3b/blob/main/finetune.ipynb) for fine-tuning (about 3 hours for 1 epoch on T4).
{"language": ["en"], "license": "gpl-3.0", "datasets": ["databricks/databricks-dolly-15k"], "pipeline_tag": "question-answering"}
question-answering en dataset:databricks/databricks-dolly-15k license:gpl-3.0 region:us
TAGS
#question-answering #en #dataset-databricks/databricks-dolly-15k #license-gpl-3.0 #region-us 


Minimal Alpaca-LORA trained with databricks/databricks-dolly-v2-15k dataset and based on OpenLLaMA-3B-600BT.

There is a pre-trained LoRA adapter and a Colab Jupyter notebook for fine-tuning (about 3 hours for 1 epoch on T4).
TAGS
#question-answering #en #dataset-databricks/databricks-dolly-15k #license-gpl-3.0 #region-us 
