Instructions to use alphaedge-ai/mt5-base-haw-16384 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alphaedge-ai/mt5-base-haw-16384 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="alphaedge-ai/mt5-base-haw-16384")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("alphaedge-ai/mt5-base-haw-16384") model = AutoModelForSeq2SeqLM.from_pretrained("alphaedge-ai/mt5-base-haw-16384") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 93f95d8f96745efea7922a680de292abb815923fbcdb995b60e71dff10bf3f28
- Size of remote file:
- 894 MB
- SHA256:
- ef214cb6c2f102d977415499156e9810add797baa0f92125201b3b7ca251d1d6
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