Instructions to use arver/t5-base-boolean-qgen-direct-finetune with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use arver/t5-base-boolean-qgen-direct-finetune with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("arver/t5-base-boolean-qgen-direct-finetune") model = AutoModelForSeq2SeqLM.from_pretrained("arver/t5-base-boolean-qgen-direct-finetune", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from arver/t5-base-boolean-qgen-direct-finetune: direct link, hf CLI and curl.
- Browser
- Download file 892 MB
-
https://huggingface.co/arver/t5-base-boolean-qgen-direct-finetune/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://arver/t5-base-boolean-qgen-direct-finetune/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/arver/t5-base-boolean-qgen-direct-finetune/resolve/main/pytorch_model.bin
892 MB
- Xet hash:
- 9abd5b60667c9298021b9a8dc885753d78cd6e97d2f3e35b0d16b39d68916281
- Size of remote file:
- 892 MB
- SHA256:
- 801efb284aa0c12d3de04281bb0d2df0c42895373755a98cd6e88e172a150b55
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.