Instructions to use zcahyj4/lab2_efficient with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zcahyj4/lab2_efficient with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("zcahyj4/lab2_efficient") model = AutoModelForSeq2SeqLM.from_pretrained("zcahyj4/lab2_efficient", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from zcahyj4/lab2_efficient: direct link, hf CLI and curl.
- Browser
- Download file 299 MB
-
https://huggingface.co/zcahyj4/lab2_efficient/resolve/main/model.safetensors
- Command line
-
hf download hf://zcahyj4/lab2_efficient/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/zcahyj4/lab2_efficient/resolve/main/model.safetensors
299 MB
- Xet hash:
- f0b46a70e662e51859aed7e129ed9e52ed0277c3b0914271c2649671b2e42cfa
- Size of remote file:
- 299 MB
- SHA256:
- 7722e77f00d49defe609656401a77115240850947d5657b94dbc3bd647e10370
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.