dolly

Getting Started with Response Generation

If you'd like to simply test the model without training, the model is available on Hugging Face as databricks/dolly-v2-12b.

To use the model with the transformers library on a machine with A100 GPUs:

from transformers import pipeline
import torch

instruct_pipeline = pipeline(model="databricks/dolly-v2-12b", torch_dtype=torch.bfloat16, trust_remote_code=True, device_map="auto")

You can then use the pipeline to answer instructions:

instruct_pipeline("Explain to me the difference between nuclear fission and fusion.")

Getting Started with Training

• Add the dolly repo to Databricks (under Repos click Add Repo, enter https://github.com/databrickslabs/dolly.git, then click Create Repo).
• Start a 13.x ML (includes Apache Spark 3.4.0, GPU, Scala 2.12) or later single-node cluster with node type having 8 A100 GPUs (e.g. Standard_ND96asr_v4 or p4d.24xlarge). Note that these instance types may not be available in all regions, or may be difficult to provision. In Databricks, note that you must select the GPU runtime first, and unselect "Use Photon", for these instance types to appear (where supported).
• Open the train_dolly notebook in the Repo (which is the train_dolly.py file in the Github dolly repo), attach to your GPU cluster, and run all cells. When training finishes, the notebook will save the model under /dbfs/dolly_training.