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How to choose a model
Use this guide when you want to choose which model checkpoint BatDetect2 loads.
You can choose a model in both the CLI and the Python API.
Where you can choose the model
In the CLI, use --model with commands that load a checkpoint, including:
batdetect2 processbatdetect2 evaluatebatdetect2 trainbatdetect2 finetune
In Python, pass the model source to BatDetect2API.from_checkpoint(...).
If you do not choose a model, BatDetect2 uses the built-in default UK model.
Use a local checkpoint path
Use a local path when you already have a checkpoint file on disk.
CLI example:
batdetect2 process directory \
path/to/audio \
path/to/outputs \
--model path/to/model.ckpt
Python example:
from batdetect2.api_v2 import BatDetect2API
api = BatDetect2API.from_checkpoint("path/to/model.ckpt")
Use a bundled checkpoint alias
BatDetect2 also supports bundled checkpoint aliases.
The built-in UK model is available as uk_same.
The alias batdetect2_uk_same also works.
CLI example:
batdetect2 process directory \
path/to/audio \
path/to/outputs \
--model uk_same
Python example:
from batdetect2.api_v2 import BatDetect2API
api = BatDetect2API.from_checkpoint("uk_same")
Use a Hugging Face URI
You can also load a checkpoint from Hugging Face with a URI like:
hf://owner/repo/path/to/model.ckpt
This needs the optional Hugging Face dependency to be installed.
For example, install it with pip install batdetect2[huggingface].
CLI example:
batdetect2 process directory \
path/to/audio \
path/to/outputs \
--model hf://owner/repo/path/to/model.ckpt
Python example:
from batdetect2.api_v2 import BatDetect2API
api = BatDetect2API.from_checkpoint(
"hf://owner/repo/path/to/model.ckpt"
)
Choose the right source
- Use a local path when you already have a checkpoint file.
- Use an alias when you want one of the bundled models.
- Use a Hugging Face URI when the checkpoint lives in a Hugging Face repo.
Related pages
- Run inference on a folder:
{doc}
../tutorials/run-inference-on-folder BatDetect2APIreference: {doc}../reference/api- Process command reference:
{doc}
../reference/cli/predict - Train a custom model:
{doc}
../tutorials/train-a-custom-model - Fine-tune from a checkpoint:
{doc}
fine-tune-from-a-checkpoint