Instructions to use heriopaz/HalfCheetah-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use heriopaz/HalfCheetah-v3 with Transformers:
# Load model directly from transformers import AutoTokenizer, TrainableDT tokenizer = AutoTokenizer.from_pretrained("heriopaz/HalfCheetah-v3") model = TrainableDT.from_pretrained("heriopaz/HalfCheetah-v3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4a1e9ed561f0b173adb469f06257a3134254bfb48674180dee99c3b53d6616e2
- Size of remote file:
- 8.19 MB
- SHA256:
- eb860177e163dd2a0d4183f156cd37968c049143341958f73bdbbdb386889802
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.