Instructions to use sumanthbhargava/mt5-base-encoding-correction-10k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sumanthbhargava/mt5-base-encoding-correction-10k with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("sumanthbhargava/mt5-base-encoding-correction-10k") model = AutoModelForSeq2SeqLM.from_pretrained("sumanthbhargava/mt5-base-encoding-correction-10k", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download test_set.jsonl from sumanthbhargava/mt5-base-encoding-correction-10k: direct link, hf CLI and curl.
- Browser
- Download file 608 kB
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https://huggingface.co/sumanthbhargava/mt5-base-encoding-correction-10k/resolve/main/test_set.jsonl
- Command line
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hf download hf://sumanthbhargava/mt5-base-encoding-correction-10k/test_set.jsonl
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curl -L -o test_set.jsonl https://huggingface.co/sumanthbhargava/mt5-base-encoding-correction-10k/resolve/main/test_set.jsonl
608 kB
File too large to display, you can check the raw version instead.