Instructions to use cosmicshubham/checkpoints with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cosmicshubham/checkpoints with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("cosmicshubham/checkpoints") model = AutoModelForSeq2SeqLM.from_pretrained("cosmicshubham/checkpoints", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from cosmicshubham/checkpoints: direct link, hf CLI and curl.
- Browser
- Download file 32.2 MB
-
https://huggingface.co/cosmicshubham/checkpoints/resolve/main/tokenizer.json
- Command line
-
hf download hf://cosmicshubham/checkpoints/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/cosmicshubham/checkpoints/resolve/main/tokenizer.json
32.2 MB
- Xet hash:
- 5c0c46653edcd44380a03f5bd1add5823b1d64ffc4c147822a4caf2bcdd77fca
- Size of remote file:
- 32.2 MB
- SHA256:
- d0b19a6e82244e4dee3b8ecf2fc1382c7bdc4a495f0f2fda09140b56c3b4be9c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.