Instructions to use kertob/falcon_drone_commands with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use kertob/falcon_drone_commands with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("vilsonrodrigues/falcon-7b-instruct-sharded") model = PeftModel.from_pretrained(base_model, "kertob/falcon_drone_commands") - Notebooks
- Google Colab
- Kaggle
Download sample_data/mnist_train_small.csv from kertob/falcon_drone_commands: direct link, hf CLI and curl.
- Browser
- Download file 36.5 MB
-
https://huggingface.co/kertob/falcon_drone_commands/resolve/main/sample_data/mnist_train_small.csv
- Command line
-
hf download hf://kertob/falcon_drone_commands/sample_data/mnist_train_small.csv
-
curl -L -o mnist_train_small.csv https://huggingface.co/kertob/falcon_drone_commands/resolve/main/sample_data/mnist_train_small.csv
36.5 MB
- Xet hash:
- 7abf407e9f8c5c70bc35de579582b5ba02a7ede091389676b21fe7305042e068
- Size of remote file:
- 36.5 MB
- SHA256:
- 1ef64781aa03180f4f5ce504314f058f5d0227277df86060473d973cf43b033e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.