Instructions to use FINDA-FIT/mT5_Large_False_SentFin_None_None with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FINDA-FIT/mT5_Large_False_SentFin_None_None with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("FINDA-FIT/mT5_Large_False_SentFin_None_None") model = AutoModelForSeq2SeqLM.from_pretrained("FINDA-FIT/mT5_Large_False_SentFin_None_None", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e6f8d7acc121ce285fdd7ae7b9cb8c94d4251f34ec17829663e4335b2476e0d0
- Size of remote file:
- 4.92 GB
- SHA256:
- a40729e60e8cfd1fc557effd27d7a67eec7b03bcac8cdb6503557892c16927ee
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