Instructions to use OscarXZQ/tracking_shuffled_objects_five_objects with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use OscarXZQ/tracking_shuffled_objects_five_objects with PEFT:
from peft import PeftModel from transformers import AutoModelForSeq2SeqLM base_model = AutoModelForSeq2SeqLM.from_pretrained("google/flan-t5-large") model = PeftModel.from_pretrained(base_model, "OscarXZQ/tracking_shuffled_objects_five_objects") - Notebooks
- Google Colab
- Kaggle
Download web_of_lies/checkpoint-250/optimizer.pt from OscarXZQ/tracking_shuffled_objects_five_objects: direct link, hf CLI and curl.
- Browser
- Download file 38 MB
-
https://huggingface.co/OscarXZQ/tracking_shuffled_objects_five_objects/resolve/main/web_of_lies/checkpoint-250/optimizer.pt
- Command line
-
hf download hf://OscarXZQ/tracking_shuffled_objects_five_objects/web_of_lies/checkpoint-250/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/OscarXZQ/tracking_shuffled_objects_five_objects/resolve/main/web_of_lies/checkpoint-250/optimizer.pt
38 MB
- Xet hash:
- e3ddb6ce9c244005949d0b46af147edab205ed346a4bf0a1d87072cc85bd00aa
- Size of remote file:
- 38 MB
- SHA256:
- 1928db8b57883e4f77d37844ffcd26bce53ed60b4769e33c5a9e31a34c744368
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