Use Fine Tuning
You can simply use a pre-trained model on ImageNet, as this data set has multiple snakes classes.
Then you can fine tune the model with your own small data set and outputs.
See this for further understanding :
Fine Tuning in Keras
(if you don't use Keras, there are other tutorials on the internet using other Machine Learning framework)
The idea is just removing the last layer (1000 outputs if you use a model pre-trained with ImageNet) and adding a layer of your choice with random weights and a custom number of outputs (number of your classes).
Then your retrain your network, in general we retrained only the last layers (as first layers have more general features).