Instructions to use Glowcodes/mt5-small-finetuned-codeswitch with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Glowcodes/mt5-small-finetuned-codeswitch with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Glowcodes/mt5-small-finetuned-codeswitch") model = AutoModelForSeq2SeqLM.from_pretrained("Glowcodes/mt5-small-finetuned-codeswitch", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Glowcodes/mt5-small-finetuned-codeswitch: direct link, hf CLI and curl.
- Browser
- Download file 16.3 MB
-
https://huggingface.co/Glowcodes/mt5-small-finetuned-codeswitch/resolve/main/tokenizer.json
- Command line
-
hf download hf://Glowcodes/mt5-small-finetuned-codeswitch/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Glowcodes/mt5-small-finetuned-codeswitch/resolve/main/tokenizer.json
16.3 MB
- Xet hash:
- a39fc7cc9fa07a2000edfb6f0d5d52562f760e23fc530da9a345e8b496e5495f
- Size of remote file:
- 16.3 MB
- SHA256:
- cd38144ed4e51886247b55a7fd9b6fcca7afd7355345b522149ba074b455f2cb
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