Instructions to use edithram23/Redaction with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use edithram23/Redaction with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("edithram23/Redaction") model = AutoModelForSeq2SeqLM.from_pretrained("edithram23/Redaction", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download rng_state.pth from edithram23/Redaction: direct link, hf CLI and curl.
- Browser
- Download file 14.2 kB
-
https://huggingface.co/edithram23/Redaction/resolve/main/rng_state.pth
- Command line
-
hf download hf://edithram23/Redaction/rng_state.pth
-
curl -L -o rng_state.pth https://huggingface.co/edithram23/Redaction/resolve/main/rng_state.pth
14.2 kB
- Xet hash:
- 7028823a8b1d956fbd7ff90c4f152b743468b89d7bdeac3c4b8f1e3f7eeaf2db
- Size of remote file:
- 14.2 kB
- SHA256:
- de3f37dce0da17968fb3a00416110763470946455b488bf1dcd630ad0c37ecb2
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.