Robotics
Transformers
Safetensors
English
prts_qwen3_vl
image-feature-extraction
vision-language-action
vla
contrastive-reinforcement-learning
goal-conditioned-rl
qwen3-vl
prts
custom_code
Instructions to use TeleEmbodied/PRTS-4B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TeleEmbodied/PRTS-4B with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("TeleEmbodied/PRTS-4B", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- acc5c8e021c93b18c582f1654123fcdb22017ef12289398c6864def42e126cc8
- Size of remote file:
- 9.81 kB
- SHA256:
- 400af616c02e6ae8f34a358781f2a5d2158b3110c8a0c48d6f9e536c95fdc133
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