Instructions to use ranjankn/customer-support-aspect-extractor-mt5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ranjankn/customer-support-aspect-extractor-mt5 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ranjankn/customer-support-aspect-extractor-mt5") model = AutoModelForSeq2SeqLM.from_pretrained("ranjankn/customer-support-aspect-extractor-mt5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from ranjankn/customer-support-aspect-extractor-mt5: direct link, hf CLI and curl.
- Browser
- Download file 16 MB
-
https://huggingface.co/ranjankn/customer-support-aspect-extractor-mt5/resolve/main/tokenizer.json
- Command line
-
hf download hf://ranjankn/customer-support-aspect-extractor-mt5/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/ranjankn/customer-support-aspect-extractor-mt5/resolve/main/tokenizer.json
16 MB
- Xet hash:
- b89f3c4380edd111d22f41caeb0e193fb40a0c2a235a247349d16ca444bee802
- Size of remote file:
- 16 MB
- SHA256:
- 8adeccb1a674329bdfdaacd81e729e2bbaff8a58d838ec1ec9a1f612b0b00c89
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