Instructions to use Chirayu/mt5-multilingual-sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Chirayu/mt5-multilingual-sentiment with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Chirayu/mt5-multilingual-sentiment") model = AutoModelForSeq2SeqLM.from_pretrained("Chirayu/mt5-multilingual-sentiment", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Chirayu/mt5-multilingual-sentiment: direct link, hf CLI and curl.
- Browser
- Download file 1.2 GB
-
https://huggingface.co/Chirayu/mt5-multilingual-sentiment/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Chirayu/mt5-multilingual-sentiment/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Chirayu/mt5-multilingual-sentiment/resolve/main/pytorch_model.bin
1.2 GB
- Xet hash:
- 3ef6ac23606aa0f6dd7f156b65897d09bfac3cf38d747ddc88c45887864f3a7f
- Size of remote file:
- 1.2 GB
- SHA256:
- 53f148a331372bd4e2f0c0cab21f6bbbeaf0cc0f96fd6dddd951a6bc2d18adbd
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