Instructions to use meghas/mt5-small-eng with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use meghas/mt5-small-eng with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("meghas/mt5-small-eng") model = AutoModelForSeq2SeqLM.from_pretrained("meghas/mt5-small-eng", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from meghas/mt5-small-eng: direct link, hf CLI and curl.
- Browser
- Download file 16.3 MB
-
https://huggingface.co/meghas/mt5-small-eng/resolve/main/tokenizer.json
- Command line
-
hf download hf://meghas/mt5-small-eng/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/meghas/mt5-small-eng/resolve/main/tokenizer.json
16.3 MB
- Xet hash:
- 7e28529b531d80c414a5afabe44eadecedf15d80a5472b79496adea8795bbda4
- Size of remote file:
- 16.3 MB
- SHA256:
- facfaad7e41f539e5cd9a66fc15ba18493099d8487b192a474f3e026bfdf633c
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