Instructions to use ceggian/bert_post_trained_reddit_batch64 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ceggian/bert_post_trained_reddit_batch64 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForPreTraining tokenizer = AutoTokenizer.from_pretrained("ceggian/bert_post_trained_reddit_batch64") model = AutoModelForPreTraining.from_pretrained("ceggian/bert_post_trained_reddit_batch64", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ceggian/bert_post_trained_reddit_batch64: direct link, hf CLI and curl.
- Browser
- Download file 440 MB
-
https://huggingface.co/ceggian/bert_post_trained_reddit_batch64/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://ceggian/bert_post_trained_reddit_batch64/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ceggian/bert_post_trained_reddit_batch64/resolve/main/pytorch_model.bin
440 MB
- Xet hash:
- 2e2452b009f8ff6ef9ecb901d3a3dc01b00a4c4f2ddc3b3894b4794371e29707
- Size of remote file:
- 440 MB
- SHA256:
- fd76756f1d0205975513bf3b944b751f6eb55a830cc610300c3b5ebd9aedd60e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.