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 tf_model.h5 from Glowcodes/mt5-small-finetuned-codeswitch: direct link, hf CLI and curl.
- Browser
- Download file 2.23 GB
-
https://huggingface.co/Glowcodes/mt5-small-finetuned-codeswitch/resolve/main/tf_model.h5
- Command line
-
hf download hf://Glowcodes/mt5-small-finetuned-codeswitch/tf_model.h5
-
curl -L -o tf_model.h5 https://huggingface.co/Glowcodes/mt5-small-finetuned-codeswitch/resolve/main/tf_model.h5
2.23 GB
- Xet hash:
- 2b9f5c7a1a276b35479bf4c34418a03759988db6bf460b494e7c07236b50d27d
- Size of remote file:
- 2.23 GB
- SHA256:
- cfac0227303b4384503a51c150e71e7ce3b581f072240ba9035eecba169ebd8f
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