Instructions to use HARSHU550/Grammer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HARSHU550/Grammer with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("HARSHU550/Grammer") model = AutoModelForSeq2SeqLM.from_pretrained("HARSHU550/Grammer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from HARSHU550/Grammer: direct link, hf CLI and curl.
- Browser
- Download file 2.55 MB
-
https://huggingface.co/HARSHU550/Grammer/resolve/main/tokenizer.json
- Command line
-
hf download hf://HARSHU550/Grammer/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/HARSHU550/Grammer/resolve/main/tokenizer.json
2.55 MB
File too large to display, you can check the raw version instead.