Reinforcement Learning
Transformers
Safetensors
jat
text-generation
atari
babyai
metaworld
mujoco-ant
mujoco
custom_code
Eval Results (legacy)
Instructions to use jat-project/jat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jat-project/jat with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("jat-project/jat", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from jat-project/jat: direct link, hf CLI and curl.
- Browser
- Download file 2.11 MB
-
https://huggingface.co/jat-project/jat/resolve/refs%2Fpr%2F1/tokenizer.json
- Command line
-
hf download hf://jat-project/jat@refs/pr/1/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/jat-project/jat/resolve/refs%2Fpr%2F1/tokenizer.json
2.11 MB
File too large to display, you can check the raw version instead.