Instructions to use anjalyjayakrishnan/hi_do_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anjalyjayakrishnan/hi_do_model with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("anjalyjayakrishnan/hi_do_model") model = AutoModelForSeq2SeqLM.from_pretrained("anjalyjayakrishnan/hi_do_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from anjalyjayakrishnan/hi_do_model: direct link, hf CLI and curl.
- Browser
- Download file 17.3 MB
-
https://huggingface.co/anjalyjayakrishnan/hi_do_model/resolve/main/tokenizer.json
- Command line
-
hf download hf://anjalyjayakrishnan/hi_do_model/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/anjalyjayakrishnan/hi_do_model/resolve/main/tokenizer.json
17.3 MB
- Xet hash:
- 4a44dd911fe338bf5ad696129ed31b770218651a701fca058431a496c9611a14
- Size of remote file:
- 17.3 MB
- SHA256:
- 294db578d0be5b1f476fde9895a3f728d162e4d039816b3a705f352f5c5bb283
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.