Instructions to use stefanj0/t5gemma-math-corrector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use stefanj0/t5gemma-math-corrector with PEFT:
from peft import PeftModel from transformers import AutoModelForSeq2SeqLM base_model = AutoModelForSeq2SeqLM.from_pretrained("google/t5gemma-s-s-ul2-it") model = PeftModel.from_pretrained(base_model, "stefanj0/t5gemma-math-corrector") - Transformers
How to use stefanj0/t5gemma-math-corrector with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("stefanj0/t5gemma-math-corrector", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from stefanj0/t5gemma-math-corrector: direct link, hf CLI and curl.
- Browser
- Download file 34.4 MB
-
https://huggingface.co/stefanj0/t5gemma-math-corrector/resolve/main/tokenizer.json
- Command line
-
hf download hf://stefanj0/t5gemma-math-corrector/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/stefanj0/t5gemma-math-corrector/resolve/main/tokenizer.json
34.4 MB
- Xet hash:
- de8120a8a5ad8f58e471def2a751a4ff87f6d4b1fb08456bef525eed0ca8fad4
- Size of remote file:
- 34.4 MB
- SHA256:
- a975b59558425fd31428b98f13e2f928c7b79eef55c2fb358d9cd68d7ca65a3f
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